DE102015205135A1 - Method for determining a degree of automation that can be used for an at least partially automated movement of the vehicle - Google Patents

Abstract

Method for determining a usable degree of automation for an at least partially automated movement of a vehicle in the near future for at least one specific road area relevant to the movement of the vehicle and / or for at least one specific time interval in the near future, in the first data of an outdoor sensor be detected in a specific detection range and in which dependent on the first data, second data are determined, representing at least one object constellation and / or a free space area, and in which determines from the second data at least one usable for an at least partially automated movement of the vehicle degree of automation becomes. Furthermore, at least one determined usable degree of automation can be used for a plurality of different purposes in the vehicle, in particular in connection with at least one driver assistance system of the vehicle.

Description

The invention relates to a method and a device for determining a degree of automation that can be used for an at least partially automated movement of the vehicle.

Many systems are known for automating the movement of a vehicle. For example, driver assistance systems may inform the driver of the vehicle, e.g. B. warn in the event of danger, or assist in his trajectory task by controlling or regulating interventions in the chassis of the vehicle. The support of the driver by such systems ranges from the provision of a pure information offer to the driver or more easily controllable control interventions in the chassis of the vehicle to a fully automatic driver-independent control ("autonomous driving") of the vehicle.

• – manuelles Fahren mit einer Unterstützung durch eine Information
• – assistiertes Fahren
• – teilautomatisiertes Fahren
• – hochautomatisiertes Fahren
• – vollautomatisiertes Fahren

Such systems offer a very different degree of automation, z. B.

• - manual driving with a support by an information
• - assisted driving
• - semi-automated driving
• - highly automated driving
• - fully automated driving

When the driver is assisted by driver assistance systems, information about the current situation in the immediate surroundings of the vehicle is usually derived from the information captured by the vehicle sensor system. Depending on the situation, information is output to the driver of the vehicle or regulatory interventions are performed. An interpretation of available situation data is usually provided by each driver assistance system itself. As a rule, the situation interpretation therefore takes place when the driver assistance system is activated and refers to a driving maneuver already in progress.

This is also an additional use of navigation data and / or external data so-called car-to-car systems (data transfer from one vehicle to another vehicle) or car-to-infrastructure systems (data transfer from an infrastructure device, in particular from a so-called backend system ) known.

For example, the DE 10 2013 205 392 A1 relates to the field of such driver assistance systems with increasing degree of automation. Here, an automated driving, which is implemented by means of backend devices (also called "Car2X systems") for providing vehicle-external data, is in focus. With such backend devices statistical data, in particular for autonomous driving, z. B. Infrastructure data for a section of the route, which relate to the course of the lane or the lane in a global coordinate system, loaded into an in-vehicle memory. Conceivable statistical data can be z. B. refer to the characteristics of the road or the traffic flow. With the aid of a positioning system, the current position of the vehicle is related to the infrastructure data in order to calculate setpoint values for different control circuits of the automatic vehicle guidance system and to base it on the regulation. The infrastructure data is provided by a server and loaded via a radio link into the memory of the vehicle.

The actual degree of automation (without significant increase in the risks) of the degree of automation of the systems known from the prior art can vary depending on a number of boundary conditions, e.g. As of specific traffic situations, characteristics of the traffic, special construction situations, behavior of other road users in the environment, the quality of navigation data, the (typically very lack of) real-time capability of external data, etc., be very variable. The degree of automation, which can actually be used with such systems, can be at least temporarily very limited in comparison to the degree of automation theoretically achievable with the system.

The driver of a vehicle experiences an unexpected limitation of the degree of automation (even for a short period or distance) as very negative. A possibility for the intermediate increase of the degree of automation is often not used by the driver, especially if he can not be confident that the higher degree of automation is supported stably over a longer time interval. Overall, the driver often experiences the variability of the degree of automation (which is not always plausible for him) much more negatively than a low but constant degree of automation.

Furthermore, during a highly automated driving operation of the vehicle a reduced alertness of the driver is to be expected, since this can sometimes be distracted by secondary tasks or communication or can be very relaxed. A short-term change, in particular a strong and, according to the state of the art, mostly unpredictable lowering of the degree of automation, can therefore lead to a severe restriction of the driver's safety, driving comfort and confidence in automated driving.

A sufficiently reliable foreknowledge of future changes in the Degree of automation is hardly possible according to the prior art.

It is therefore the object of the invention to provide a method and a device for determining a degree of automation that can be used for an at least partially automated movement of the vehicle with respect to at least one relevant roadway area or at least one specific time interval in the near future.

This object is achieved by the subject matters of the independent claims. Dependent claims are advantageous developments of the invention.

A method is proposed for determining a degree of automation for an at least partially automated movement of a vehicle for at least one specific road area relevant to the movement of the vehicle and / or for at least one specific time interval in the near future, in which first data of an external sensor in one defined detection range are detected and second data are determined depending on the first data representing at least one object constellation and / or a free space area and from the second data at least one is used for an at least partially automated movement of the vehicle usable degree of automation.

The first data of the external sensor system may be, for example, sensor raw data or pre-processed and / or selected sensor data according to predetermined criteria. For example, this can be image data, laser scanner data or object lists, object contours or so-called point clouds (which represent, for example, an arrangement of specific object parts or object edges). Depending on the first data, second data are determined that represent at least one specific object constellation and / or a specific free space area (within a roadway area). In this case, the second data from the first data according to predetermined criteria, eg. B. by image processing or object detection, are determined. These can be z. B. reduced compared to the first data by a factor of 5-500, in particular interpreted, reduced to representing the object constellations and / or free space information.

The term lane area refers in particular to certain areas of the carriageway in the vicinity of the vehicle which are characterized by their position or shape. A lane area may also be a specific area of a lane, sector of a roundabout, etc. Lane areas may be in particular lane sections.

Lane areas may be defined by a specific information representing the space, e.g. B. absolute or relative coordinates, z. B. in terms of their boundaries, centers, etc, or be represented when determining the assignment. Roadway areas can represent an almost arbitrarily defined (area) area on a roadway, z. As a sector of a roundabout, an exit or a lane area to perform certain maneuvers, eg. B. springing or lane change maneuvers.

The usable degree of automation is, in particular, the mail of the (reliably executable) support of the driver of the vehicle with regard to his or her web guiding task or a partial takeover of his or her web guiding task. One or more usable degrees of automation determined in this way relate to at least one specific, relevant roadway area or to at least one specific time interval in the near future.

The usable degree of automation is, in particular, a prediction of the degree of automation which can be carried out sufficiently well and / or of a degree of automation which can be carried out with a sufficiently high degree of probability. In other words, the degree of automation can be defined in particular as the maximum possible degree of automation, in which an availability and / or risk or probability of an at least partially automated movement of the vehicle remains or remain below predefined criteria or dimensions.

The degree of automation that can be used can be understood as a proportion of driver tasks which are automated or can be carried out in relation to a specific lane area and / or a specific time interval in the near future, or as the ratio of the automatically executable driver tasks to that of Driver to take over driving tasks. Alternatively or additionally, the usable degree of automation may also include a degree of availability of the partially automated movement of the vehicle (in relation to the roadway area and / or the time interval).

The usable degree of automation may additionally refer to the means for driving automation available or to be activated or activated in the vehicle. It is also possible with these means and possibly in a specific environment (highway, highway, parking) maximum achievable degree of automation be taken into account. Also further vehicle-specific and / or driver-specific circumstances can be taken into account when determining the usable degree of automation.

The usable degree of automation of an at least partially automated movement of a vehicle can be determined in the form of a plurality of values that represent a respective measure of a possible (usable) automation of different driving functions or driver assistance systems.

In this case, the ascertained degree of automation related to the near future can be expressed in the form of one or more qualitative and / or quantitative measures or in the form of a scientific context (eg as a formula), in particular depending on a location information and / or time information and Vehicle for different purposes, in particular for a driver assistance system, are provided or used.

A particular relevant for the movement of the vehicle lane area may, for. B. be in the near future to be traveled or passable certain driving range (eg, about 50-200 meters in front of the vehicle). A lane area may be a portion of a lane of a multi-lane carriageway, a part of a roundabout, turning area, parking lot or parking garage, etc.

At least one particular time interval may be a time interval in the near future in which the performance of a (particular) maneuver is necessary or probable. Such a time interval may be a time interval which is dependent on the driver's maneuver planning of the data of a driver assistance system or of the current route planning of a navigation system.

The roadway area that is relevant for the movement of the vehicle may, but need not, correspond to the detection area of the exterior sensor system. It can be within the coverage area or partially overlap with it. The relevant roadway area may also lie in the direction of travel in front of the detection area of the exterior sensor system.

Properties of object constellations and free space areas at one or more time intervals in the near future may be dependent on their properties at an earlier time, e.g. At a current time or a time a few seconds before the current time.

In this case, the object constellations and / or free space regions can be detected at a first time in a first roadway area and in particular can be represented together with their properties. Depending on this, positions and properties of object constellations and / or free space regions can be determined at a second time in a second roadway area, in particular in the relevant roadway area.

The usable degree of automation can be determined as a function of the object constellations predicted or simulated in the context of the method, which the vehicle can or would form together with other objects in the event of driving on certain lane areas at specific time intervals.

The usable degree of automation can also be determined depending on a pre-determined and / or stored in a database information that includes the degree of usable degree of automation depending on certain types of object constellations or properties of object constellations that meet predetermined criteria. In this case, the achievable degree of automation can also be determined as a function of the pre-determined or simulated properties of object constellations and / or free space areas for specific time intervals in the near future which the vehicle would form together with other objects in the event of driving certain roadway area at specific time intervals. Among other things, the prior knowledge about the behavioral characteristics of road users in certain object constellations, in particular formations, can be taken into account.

In particular, known methods of probability theory or the simulation of object movements or of human behavior in traffic can be used in the method.

It is particularly advantageous to determine the usable degree of automation, which relates to one or more combinations of at least one specific road area relevant to the movement of the vehicle and to at least one specific time interval in the near future. Depending on one or more such combinations, a driving function of the vehicle, for. B. motion planning of the vehicle for the near future, to be optimized.

It is particularly advantageous to determine a sequence of two or more usable degrees of automation for at least two lane sections or vehicle positions within a lane section or for at least two specific time intervals.

It is very particularly preferred to determine a (temporal and / or spatial) progression function of the degree of automation for one or more lane sections or vehicle positions relevant to the movement of the vehicle within a lane section or within one or more time intervals.

Particularly preferably, a sequence of degrees of automation and / or a course function of the usable degree of automation (according to space and / or time) is determined, which relates to a plurality of lane areas and / or time intervals. It is possible to assign a respective roadway area, a time interval and the determined usable degree of automation in various combinations to one another. As a result of the assignment can, for. B. a scientific, in particular mathematically expressed function, eg. As a lock-up table result, which expresses possible associations between lane areas and / or time intervals and / or usable degrees of automation. The resulting assignment can also be used for other purposes in connection with driving functions or the operation of the vehicle.

Particularly preferred is the determination of at least one degree of automation in the form of a class (category value) from a limited set of predefined classes. Such classes can z. B. from the art known classes correspond:
A1: "assisted driving",
A2: "semi-automated driving",
A3: "highly automated driving",
A4: "fully automated driving"
This can be in the professional world (eg by the VDA = Association of German Automobile Manufacturers) known and recognized gradations of the degree of automation.

Particularly preferably, category values are chosen such that they require different degrees of driver involvement. Thus, the determined degree of automation receives an additional value for the driver, as soon as such a gradation understandable to the driver is displayed.

In addition, an important part of the invention is that certain aspects or measures or criteria of the usable degree of automation can be determined individually. In particular, it deals with aspects that are at least partially independent of each other suitable for a particular driving profile.

• – Längsführung des Fahrzeugs und/oder
• – Querführung des Fahrzeugs und/oder
• – Durchführung eines Spurwechsels und/oder
• – Durchführung eines Überholvorgangs und/oder
• – Fahrerinformation und/oder
• – Signalisierung des Fahrzeugs nach außen.

One or more usable automation levels in the near future or a course of usable automation level for the near future may relate to two or more automation parameters and / or two or more different driver assistance functions and / or two or more maneuvers and / or signaling Vehicle to the outside (separately) are determined, for. B .:

• - Longitudinal guidance of the vehicle and / or
• - Transverse guidance of the vehicle and / or
• - Carrying out a lane change and / or
• - Carrying out an overtaking process and / or
• Driver information and / or
• - Signaling the vehicle to the outside.

The signaling of the vehicle to the outside may be a signaling according to different known from the prior art and future methods, for. B. targeted sounds, lights, projections, symbols or graphics (eg., According to DE 102012219574 ), as well as radio signals to other vehicles.

An especially quantitative degree of automation, which may be determined with a high degree of accuracy, can also be assigned to one of a plurality of predefined classes in a further step of the method.

The exterior sensor system comprises at least one sensor for detecting a part of the route, in particular one or more specific lane areas. The external sensor system can comprise a plurality of sensors, wherein at least one of them can be designed to be rotatable, pivotable or tiltable. The external sensor system can also electronically change a detection range that can actually be evaluated (eg the so-called field of view). Furthermore, the method may comprise a comparison or a fusion between the data of at least two sensors of the external sensor system. Such an adjustment or such a fusion can be carried out within a computing unit of the external sensor system.

The external sensor detects a part of the environment in the defined lane area from a perspective outside the vehicle, in particular from the perspective obliquely from above, and thereby provides the first and / or second data, the one or more object constellations and / or free space areas or Represent free space area constellations within the defined lane area.

The external sensor system is, in particular, a sensor system mounted substantially above one or more defined roadway areas. This results in a significant advantage that the detection perspective resulting from such a position, a typical vehicle-related detection perspective, for. B. with regard to hidden objects and / or free space areas added. In addition, with such an external sensor system, a relatively large driving range, which leads to a performance of a maneuver, for. B. a threading maneuver or an overtaking maneuver are detected. It is also possible to detect two or more defined roadway areas with a sensor of the external sensor system.

Lane areas can be defined in the process fixed or variable depending on predetermined criteria.

Alternatively or additionally, the external sensor system may be a movable external sensor system which moves together with other vehicles, in particular in the roadway areas.

In the method, two or more external sensor data from two or more external sensor systems, for example for determining an automation grass that can be used in the near future, can also be used. As a static outdoor sensors and a movable outdoor sensors, are taken into account.

In this case, the external sensor system can also detect at least a part of the (ego) vehicle for which the usable degree of automation is determined, and the vehicle can in the first and / or second data, for. B. as an object, in particular a part of an object constellation can be represented. In this case, the vehicle, for which the usable degree of automation is determined, figuratively speaking "himself" and to the relevant for him object constellations and free space areas "see" from a sublime perspective. Thus, in the usable degree of automation determined in the method, circumstances that could not be taken into account by the vehicle from its own perspective (even assuming an ideal vehicle sensor system) can be taken into account.

In this case, the provided first and / or second data from at least one lane area can be valid in time, eg. B. also be assigned in the form of a function dependent on the time. This function may represent a validity expiration or a change (decrease) in the data confidence depending on the time.

Object constellations can be the entity of two or more moving objects that are in proximity to each other or move. In particular, an object constellation comprises objects that move in a (compared to the other traffic dynamics) substantially fixed or slowly changing formation and / or have a substantially fixed or slowly varying movement behavior relative to each other. In particular, an object constellation is characterized by a relationship of the objects to one another. Such a relationship may be a so-called swarm behavior, e.g. B. within a so-called swarming, be. Representing an object constellation in the method is advantageous because, compared to representing individual objects, it is much more economical with respect to the amount of data to be transmitted and processed. In this case, the usable degree of automation may advantageously also include, depending on the information relating to the relationship of the at least two objects to one another in an object constellation (eg of the formed movement formation).

Particularly preferably, the provided external sensor data represent one or more free space areas, preferably in the form of constellations formed from free space areas.

In the context of this patent application, a free space area is a spatial area, in particular a specific roadway area or a specific part within such a roadway area, in which no objects or objects of a particular class, e.g. B. no pedestrians or no motorcycles are located.

Representing a free space area is in many cases much more advantageous over representing individual objects or object constellations. According to the invention, the provided external sensor data may preferably represent free space areas having a size exceeding a certain extent (eg length and width), while these preferably do not represent free space areas having a size below a certain level (eg length and width) , This results in a further advantage because z. B. relatively small areas of objects-free areas must not be represented in the external data at great expense.

The free space area represented in the external sensor data can also be limited to surface areas which are larger than predetermined dimensions, for example at least as large as the areas of the free space areas which have immediate relevance for the movement of the vehicle in the near future. , Predetermined dimensions can be predefined depending on the size or shape of the vehicle. For example, dimensions are larger than dimensions of an area occupied by the vehicle (without increased risks) (occupy) can. Such an area may also include a required safety margin for at least one vehicle.

The free space area represented in the second data can in this case be limited to such a free space area that can be reached and / or assigned to the vehicle, in particular taking into account the current traffic situation or other influencing factors. The representation according to the invention of the free space regions or free space constellations in the provided second data has the advantage, inter alia, that the data to be provided can in many cases have a much smaller size (and also in comparison to data that represent objects) faster for at least one vehicle can be deployed wirelessly.

By way of example, the free space areas which are comparatively easily accessible by the vehicle (in the present traffic situation) can be represented in the second data and / or comparatively hard-to-reach free space areas can not be represented.

In this case, the determination and / or provision of the second data can be limited to those object constellations and / or free space areas which are relevant for the usable degree of automation of the vehicle, in particular on the basis of the prevailing boundary conditions, in the near future.

A free space area or a free space constellation can be represented in at least two dimensions. The representation may be in the form of vectors. For example, at least some boundaries of the free space area may be described by concatenation of multiple vectors or by a combination of one or more predefined standard forms. The representation can also be done by a combination of certain standard forms. Such standard forms can, for. As rectangles, polygons, circles, ovals or curvilinear figures or shapes. Even a complex shaped open space area can be characterized by a very compact representable information z. As the type, size, position or speed of one or more standard forms, be represented. In this case, a relatively complex geometric information about the object constellations or free space constellations must be replaced by one or more (known to the recipient) standard forms. Thus, the geometric information does not have to be transmitted every time and results in an extreme reduction of the amount of data.

A free space constellation can be formed by a spatial arrangement of at least two free space areas. In particular, a free space constellation comprises at least two free space areas which move in a substantially fixed or slowly changing formation and / or have a substantially fixed or slowly changing movement behavior relative to each other, in particular compared with the dynamics of change of a traffic event.

The second data representing a free space constellation may include information about the relationship of the at least two free space areas to each other in a free space constellation. For example, the useable degree of automation determined in the method can also include (preferably optimized) transitions from one free space area to another free space area.

An object in the method is also a part of an object. As a free space area is also a part of a (contiguous) open space area to understand.

An object can be z. B. also be represented by a facing to the respective sensor side of the object or a part of the object, which is only partially in the detection range of the sensor. Accordingly, the vehicle for which the usable degree of automation is determined can also be represented in the second data.

Particularly preferably, the provided second data also represent properties of object constellations and / or free space areas.

In an advantageous embodiment of the method, the second data represent properties of at least one object constellation and / or at least one free space area in the detection area of the exterior sensor system and / or in a specific roadway area.

• – Position und Bewegungsdaten einer Objektkonstellation,
• – Form und/oder Ausdehnung der Objektkonstellation,
• – Position der Objekte zueinander, die eine Objektkonstellation bilden,
• – Relative Bewegungsdaten der Objekte, die eine Objektkonstellation bilden, zueinander oder zu einem vordefinierten geometrischen Punkt der Objektkonstellation,
• – Objektklasse der Objekte, die eine Objektkonstellation bilden,
• – Information, die eine Formstabilität oder Formveränderung der Objektkonstellation repräsentiert,

In an advantageous embodiment of the method, the properties of at least one object constellation are determined, specifically as a function of one or more entries from the following list:

• - position and movement data of an object constellation,
• - shape and / or extent of the object constellation,
• - Position of the objects to each other, which form an object constellation,
• Relative movement data of the objects that form an object constellation, to one another or to a predefined geometric point of the object constellation,
• - object class of objects that form an object constellation,
• Information representing a dimensional stability or shape change of the object constellation,

• – Form und/oder Ausdehnung des Freiraumbereichs,
• – Position und Bewegungsdaten eines Freiraumbereichs, insbesondere der Grenzen des Freiraumbereichs,
• – Information, die eine Formstabilität oder Formveränderung des Freiraumbereichs repräsentiert.

In an advantageous embodiment of the method, the properties of at least one free space area are determined, specifically as a function of one or more entries from the following list:

• - shape and / or extent of the open space area,
• Position and movement data of a free space area, in particular the boundaries of the free space area,
• - Information that represents a dimensional stability or shape change of the free space area.

In this case, the constancy of the extent of a free space area in one or more directions can also be taken into account.

The dimensional stability can z. B. expressed as a probability value for the shape preservation or the shape change.

In this case, the usable degree of automation for a given free space area and / or for a specific time interval depending on the second data representing a property of a free space constellation, for. B. the dimensional stability of a free space constellation (which, for example, from a largely dimensionally stable "swimming" with the traffic may have up to a strong variability of shape or dimensions) are determined at an earlier time interval. In the case of dimensionally stable free space areas, the ascertainable usable degree of automation may include a higher time horizon. In the case of a non-dimensionally stable free space area, the usable degree of automation can be determined taking into account alternative free space areas.

In this case, statistical information and / or information known from behavioral research and / or group dynamics can also be used for the behavior of road users, in particular in certain (typical) formations of vehicles, in particular of motor vehicles in certain driving situations (traffic jam, flowing traffic, city traffic, etc.). ).

In particular, one or more degrees of automation in the method is / are determined as a function of predefined combinations of the properties of object constellations and / or free spaces. These are preferably those combinations of properties of the object constellations and / or properties of the free space areas, which have a special significance for the current vehicle movement, such. B. a group of pedestrians or a crossing pedestrian with a stroller.

In an advantageous embodiment of the method, two or more possible degrees of automation, which relate to at least two at least partially different road areas and / or at least two at least partially different time intervals, determined, depending on the determined degrees of automation and / or according to predetermined criteria, at least one optimized combination of at least one lane area and at least one time interval is determined.

Particularly preferably, depending on a combination determined or selected according to predetermined criteria, a movement planning for at least one vehicle (in particular the ego vehicle) can be determined.

In an advantageous embodiment of the method, the particular lane area relevant for the movement of the vehicle is determined in the near future to be traveled lane area or a lane area in which a specific maneuver in the near future can or should be performed, the information that the the roadway area to be traveled and / or the maneuver represented is determined as a function of a determined driver intention and / or from the evaluation of the current traffic situation and / or from the route planning of the vehicle.

In doing so, the means provided for or available for the implementation of the method can be used optimally by automatically orienting the method primarily to the determination of the most relevant data.

In an advantageous embodiment of the method, the first data and / or the second data are provided for a roadway area that overlaps at least partially with the particular roadway area relevant to the movement of the vehicle, and / or at least partially with respect to the direction of travel of the vehicle such a driving range is located.

In this case, the current or probable movement of the object constellations and / or free space areas in the traffic flow can also be taken into account. It is also possible to determine a quantitative information for a prediction that takes into account an anticipated or predicted movement of an object constellation and / or a free space area. The lane area to which the first and second data are provided is determined to be different depending on the traffic conditions Traffic flow, in particular depending on the determined properties of the object constellations and / or open spaces, more or less (in the direction of travel of the vehicle) in front of the relevant for the movement of the vehicle lane area in which z. B. is planned in maneuvers, is.

In other words, in a step of the method, depending on a road area (determined in the method) that is relevant for the movement of the vehicle and on properties of the object constellations or clearances (determined in the method), a specific roadway area can be determined to which the first data and / or to provide the second data. Thus, the provision of the second data may be limited to one or more lane areas that are sufficient for a statement as to how the usable degree of automation will be in a (possibly different) lane area relevant to the movement of the vehicle. Depending on the lane area thus determined, the detection range of the exterior sensor system can be changed automatically, in particular directed or restricted to specific lane areas. Thus, the amount of corresponding data to be processed and transmitted is also limited.

In an advantageous embodiment of the method, depending on the vehicle speed or on a determined or estimated time of arrival of the vehicle in a certain roadway area, the external data can be evaluated from further different specific roadway areas. Also, depending on the vehicle speed or a determined time of arrival of the vehicle in a certain lane area, in particular in a certain surface area of the lane area, an order or priority in the processing of the first and / or second data from different lane areas can be varied.

This results in an inventive advantage that the most relevant for the determination of the usable degree of automation first or second data, in particular for the respective appropriate time, are evaluated. Also, the amount of first and / or second data to be wirelessly transmitted or processed may be reduced, at least in total. In this case, the real-time capability of the method compared to other conceivable other methods can be significantly increased. Lane areas can in the process, for. B. depending on the current traffic situation, each selected for a specific time interval.

In an advantageous embodiment of the method, depending on position data and movement data of the vehicle and / or on a movement planning of the vehicle and / or in dependence on the operator actions of the driver, one or more specific lane areas or specific area areas within at least one lane area is determined for which the first and / or second data are provided.

In a further advantageous embodiment of the invention, alternatively or additionally, lane areas and / or area areas within the lane areas, to which the object constellations and / or free space areas in the first and / or second data are represented, and lane areas and / or area areas within the lane areas, to which the object constellations and / or free space areas in the data of a vehicle sensor system are represented, are controlled in dependence of each other.

It can be z. For example, an angle in which object constellations and / or free space regions (for example, from the external sensor system) are detected can be varied. By way of example, a panning camera belonging to the external sensor system can be pivoted electromechanically or electronically, depending on the extent to which a vehicle camera, for example with respect to a specific object constellation, can not or can not easily detect it. In this case, the provided first and / or second data can essentially be restricted to a required extent, which is used at the given time interval as being particularly important and / or urgent for determining the usable degree of automation. Thus, data volume, computing power and other resources can be further reduced.

Advantageously, the method can be configured as a function of an approach of the vehicle to a specific roadway area or to a roadway area of a specific type (eg an exit, tunnel, turning area, etc.).

• – eine Anfrage zum Bereitstellen von ersten und/oder zweiten Daten unmittelbar oder mittelbar versandt werden, und/oder
• – eine bestimmte Auswahl aus den bereitgestellten von ersten und/oder zweiten Daten (für eine weitere Nutzung im Verfahren) ermittelt werden.

In this case, the approach to a relevant for the movement of the vehicle lane area, in particular a structural special situation, for. B. depending on navigation data (eg, based on an entry in the navigation map, stored coordinates, a detection of certain road layout) and / or by a wireless connection (eg, WLAN, LTE, etc,) are determined. Depending on the approach to such a special situation, by means of the vehicle:

• - a request for the provision of first and / or second data is sent directly or indirectly, and / or
• A particular selection is determined from the provided first and / or second data (for further use in the method).

The determination of the usable degree of automation by means of the external sensor system preferably takes place such that the particularly urgently required supplementary first and / or second data about the vehicle-internal data, in particular about the data of the vehicle sensor system, are made available. In this case, the external first and / or second data determined in dependence on the external sensor system, in particular actively, can be selectively queried by sending a request from the vehicle.

Thus, the method may include wirelessly sending a request from the vehicle representing a reference to the first data and / or second data to be provided. In particular, the request or a corresponding request message may include specific geometric areas and time information. In this case, the query may relate to one or more specific lane areas or one or more specific parts of one or more lane areas from which these data are (primarily) required.

Advantageously, the first and / or second data provided or to be provided can be limited such that substantially only a part of them is provided or selected by means of the vehicle, which is used to determine the usable degree of automation, in particular for a sufficiently long time horizon and / or in sufficient quality is required. As a result of the invention, the quantities of data to be transferred wirelessly and to be processed in the vehicle can also be substantially reduced, which can lead to very considerable savings of resources and the radiation load.

In an advantageous embodiment of the method, at least one degree of automation is also determined as a function of the data of an internal vehicle sensor system.

The vehicle for which the movement planning according to the invention is determined can be implemented via a vehicle sensor system (on-board sensor system) with at least one sensor (camera system, laser sensor system, eg laser scanner, LED sensor system, radar sensor system, ultrasound sensor system, etc.). to capture part of its environment. The detection of the objects or object constellations and / or free space regions can take place in two dimensions or three dimensions. An extension of a two-dimensional recording with additional information on a third dimension can also be carried out (technical term: "2.5 D"). The at least one vehicle sensor can be permanently connected to the vehicle.

In dependence on the data of the vehicle sensor system from the detected part of the environment of the vehicle, internal sensor data is determined or provided which shows one or more object constellations and / or one or more free space regions in the surroundings of the vehicle, in particular from the vehicle perspective , represent.

The representation of the object constellations and / or free space areas here refers to the position and / or the movement data and / or the property and / or the state of the object constellation or free space areas.

The internal sensor data and / or the external sensor data may represent an absolute position of an object constellation and / or a relative position of one or more objects in the object constellation. An absolute position may refer to a stationary coordinate system, e.g. As well as the global coordinate system. A relative position of an object may be related to information representing the position of the object constellation (eg, a geometric centroid or other boundary of the object constellation). Thus, data volumes to be processed can be further reduced and a high compatibility potential can be achieved.

The relative positions may be in the internal sensor data and / or external sensor data respectively information about distances, angles and arrangements of an object constellation and / or a free space area in relation to the parts of the road infrastructure (lane markings, crash barriers, etc.) or specific movable or standing objects.

For example, the internal sensor data and / or the first and / or the second data may represent a plurality of parts of an object constellation and / or a free space area, for example by a so-called point cloud, a discrete-location function, an interpolated function, a polynomial or a spline. In particular, the internal sensor data and / or the external sensor data may include the information about the (spatial) boundaries of an object constellation and / or a free space area, for example positions of the area boundaries within which one or more objects are located. In this case, the internal sensor data and / or the external sensor data may contain the information about a plurality of parts of an object constellation and / or a free space area, especially beyond their borders. The detection of the object constellations and / or free space areas preferably takes place in at least two dimensions with an accuracy of less than +/- 0.5 meters.

The data of the vehicle sensor system and the first and / or second data, which are determined as a function of the exterior sensor system, preferably represent at least one object constellation and / or a free space area from substantially different spatial perspectives on a roadway area. Thus, for example, it is also possible to solve the problem that occlusions of an object by another object or by parts of the vehicle within an object constellation lead to incomplete or erroneous detection of the environment or to imprecise or erroneous prediction. Thus, even conceivable consequences of a fault of an external sensor or a vehicle sensor system can be significantly mitigated.

The vehicle sensor system and / or the external sensor system preferably detects one or more object constellations and / or one or more free space regions in at least two dimensions. For example, two dimensions in which a sensor of the external sensor, z. As a camera, multiple objects or an object constellation can represent well, perpendicular to the axis between the sensor (camera) and the object. In other words, perspectively fused (adjusted) data can be determined as a function of two internal sensor data and external sensor data, which are essentially two-dimensional from different perspectives, such that they contain information about object constellations and / or free space region constellations of three Dimensions include.

Preferably, the information about a part of an object constellation and / or a free space area may be represented in the external data, while another part may be represented to the same object constellation and / or to the same free space area in the internal data. In the process, the internal data and external data can be adjusted in such a way that properties of the object constellation and / or the free space area can be completed. In this case, the parts of objects which are remote from the respective sensors and / or concealed parts can also be sufficiently taken into account.

Preferably, the method comprises determining the perspectively fused data as a function of the internal sensor data and the first and / or second data. Perspectively fused data can be determined such that they determine the spatial nature of an object constellation partially or substantially three-dimensionally and that this is represented in the internal sensor data and / or the external sensor data. The perspectively fused data can then be reduced to fused two-dimensional data representing object constellations and / or free space areas in only two, in particular horizontal, dimensions. In this case, the internal sensor data and / or the external sensor data represent geometric projections of at least one object constellation and / or a free space area on the (corresponding) roadway areas. Thus, the amount of data to be provided can be further reduced; the advantage of the perspective fusion of the data is retained.

It can not sufficiently matching data z. B. mainly used to control non-safety-related vehicle systems or to control the vehicle movement in a small, non-safety-critical dimensions and / or only for comfort functions.

In an advantageous embodiment of the method, a determined usable degree of automation is assigned to one of a plurality of predetermined classes, each of which presupposes a certain degree of driver involvement in partially automated driving.

• – eine Information an den Fahrer ausgegeben und/oder
• – die aktuelle Bewegung des Fahrzeugs verändert und/oder
• – eine Bewegungsplanung für die nahe Zukunft ermittelt oder verändert und/oder
• – eine Manöverplanung für ein Fahrzeug ermittelt oder verändert.

In an advantageous embodiment of the method, the following is carried out depending on a determined change in the usable degree of automation in the near future or in the relevant roadway area:

• - issued information to the driver and / or
• - The current movement of the vehicle changed and / or
• A movement planning for the near future is determined or changed and / or
• - Determined or changed a maneuver planning for a vehicle.

• – eine Information an den Fahrer ausgegeben und/oder
• – die aktuelle Bewegung des Fahrzeugs verändert und/oder
• – eine Bewegungsplanung für die nahe Zukunft ermittelt oder verändert und/oder
• – eine Manöverplanung für ein Fahrzeug ermittelt oder verändert.

In an advantageous embodiment of the method, depending on the useable degree of automation determined, in particular depending on a sequence of the useable automation levels or on a history function of the usable degree of automation in the near future or in a certain relevant roadway area:

• - issued information to the driver and / or
• - The current movement of the vehicle changed and / or
• A movement planning for the near future is determined or changed and / or
• - Determined or changed a maneuver planning for a vehicle.

Depending on at least one ascertained degree of automation, it is particularly preferable to output at least one item of information to the driver of the vehicle, which represents the share of the driver and / or the proportion of the automated driver tasks, in particular at a specific time interval in the near future ,

In this case, in particular by means of suitable information or sequence of information, the so-called (technically acceptable) "driver-to-the-loop time", d. H. the time within which the driver should pick up or resume his driving duties when needed, be extended to a reasonable or more acceptable to the driver level.

Particularly preferably, a movement planning of the vehicle for the near future is determined as a function of at least one ascertained usable degree of automation or of a sequence of a plurality of degrees of automation or a course function of the degree of automation.

The movement planning may relate in particular to a possible path guidance of the vehicle, in particular longitudinal guidance and / or transverse guidance, in a near future. This can be expressed by temporal and geometric relationships.

According to an advantageous embodiment, the motion planning may comprise a sequence of two or more coordinates of the vehicle at certain time intervals in the near future. Such a sequence may represent information about the order and / or time intervals for occupying at least one respective lane area (or a position within the driving area) by the vehicle. The respective (absolute or relative) coordinates may also include an orientation of the vehicle, e.g. In relation to its current position or with respect to certain landmarks, e.g. As a traffic light, a stop line or a specific track, represent. Such positions of the vehicle can be represented in an absolute or relative coordinate system. Such a position can also refer to a particular time interval or to a specific time at which the vehicle should reach the corresponding position or the corresponding movement parameter.

Advantageously, the motion planning may relate to the movements of the vehicle in the near future, which at the present time do not require any control or intervention in the chassis of the vehicle. In other words, the motion planning data may also include movements of the vehicle that can not yet be performed at the time of determining the properties of object constellations and / or free space areas. The motion planning can also relate to a maneuver of the vehicle, which can be performed only after the current maneuver (as a successor maneuver).

In the method, the motion planning is also particularly preferably determined in such a way that an optimized course of the usable degree of automation results within a route.

It can be z. B. the motion planning, in particular in the form of certain maneuvers to be performed, be planned so that an optimized degree of automation, in particular a very high degree of automation and / or a constant as possible usable degree of automation results.

Preferably, the usable degree of automation is optimized depending on the relationships determined between relevant lane areas, time intervals and resulting degrees of automation such that an association between the lane areas to be traveled at specific time intervals is performed. However, it is also possible to make a selection from a plurality of possible sequences or courses of the degrees of automation (and resulting motion planning) according to predetermined criteria.

Advantageously, it can be determined for a current or forthcoming traffic situation, in particular taking into account planned or desired maneuvers, how high the usable degree of automation can be or may be. In this case, it can also be automatically decided in the method whether a partially automated movement of the vehicle is feasible depending on predetermined criteria. It may then be executed (in a certain lane area or at a certain time) or not executed. Thus, the possibly necessary change in the degree of automation actually to be carried out can be determined in good time and one of the measures discussed above can be taken. Thus, for the driver the surprising takeover requests of driving tasks are spared and the vehicle systems also have the necessary time for a change or finding alternative measures.

Particularly preferably, the measures discussed above for the near future are dependent on a determined, predetermined average, in particular exceeding a predetermined value Change in the determined usable degree of automation in the near future. The change in the degree of automation can relate here to the difference between the current degree of automation and a usable degree of automation determined for the near future or to the difference between two usable degrees of automation determined with respect to at least two specific lane areas or time intervals.

For example, information is output to the driver of the vehicle depending on the change in the degree of automation (determined for the near future). In this case, a decrease in the degree of automation determined for the near future preferably results in a more distinctive (at least more markedly perceptible) information to the driver than an increase in the degree of automation (determined for the near future).

The invention provides an optimized approach for determining a finely-scaled usable degree of automation that is precisely related to the near future for at least partially automated movement of the vehicle. The method may be carried out depending on or also independently of the implementation of the automation of the movement of the vehicle (actual control or regulation). The automation of the movement itself can also z. B. based solely on the vehicle sensors. In this case, the automation or the degree of automation of the vehicle movement can be controlled or influenced as a function of parameters of the usable (or optimized) degree of automation determined in the method. Thus, the potential of the driver assistance functions, which are designed for automated movement, can be optimally utilized.

Depending on a determined course of the usable degree of automation or certain pre-determined changes in the usable degree of automation, many other displays, actuators and safety systems of the vehicle can be controlled.

In the method, an automatic change of the degree of automation with respect to the movement of the vehicle in a roadway area and / or in a specific time interval in the near future depending on the usable degree of automation determined in each case may also preferably take place.

Lane areas may be considered as lane areas (eg, lane sections) that are comparable to or larger than the dimensions of the vehicle. These can be z. B. also be of their size or dimensions with a required space to perform a maneuver or smaller. Preferably, the spatial areas are 0-30 meters, 20-200 meters, 200-500 meters or further away from the vehicle, especially in its direction of travel. Advantageously, there is at least one time interval to which at least one usable degree of automation relates within the next 0 seconds or 0.2 to 5 seconds. Such a chosen "near future" is also particularly important because it refers to a time interval (time horizon), during which the driver of the at least partially automated vehicle usually can not (re-) record the driving task. Determining the expected degree of automation for this time interval, z. B. for two alternative tracks and / or maneuvers, is very advantageous because this corresponds to a takeover time of the vehicle management tasks by the driver of the vehicle. Advantageously, at least one time interval is within the next 5 to 30 seconds. In this case, the determined degree of automation can essentially relate to a (virtually complete) time span of a maneuver.

Particularly preferably, the determined usable degree of automation relates to a roadway area and / or a time interval in the near future in which no regulation of the movement of the vehicle with the vehicle sensor system can be carried out or determined yet.

In the method, it is also preferable to determine a feasibility of a particular maneuver with a certain degree of automation, in particular in relation to the degree of automation currently being performed or expected by the driver. Depending on this, information can be output to the driver.

For example, it can be determined whether a maneuver, in particular for a substantial amount of time of the maneuver, can be carried out without a significant drop in the degree of automation.

Preferably, an optimized usable degree of automation can be determined, which depends on predetermined criteria, in particular on the specifications of the driver, on the stored operating history of the driver or the vehicle or on further criteria (eg road type). Thus, an adaptation of the method to the concrete needs is achieved.

• – Unterstütztes Fahren
• – Teilautomatisiertes Fahren
• – Hochautomatisiert Fahren
• – Automatisches Fahren.

Solche Klassen haben den Vorteil, dass diese für den Fahrer verständlich sind und sie können diesem auch angezeigt werden.In one embodiment of the invention, the z. B. executed by a driver assistance system of the vehicle or to be executed degree of automation of the vehicle depending on determined usable degrees of automation at least partially automatically varied. In this case, in particular, an optimal time profile of the degree of automation in an area (in particular route section) can be achieved. Advantageously, the degree of automation of the at least partially automated movement of the vehicle within the lane section can be varied almost continuously or in steps depending on the determined optimized usable degree of automation, in particular between a plurality of predefined classes, eg. B .:

• - Supported driving
• - Partially automated driving
• - Highly automated driving
• - Automatic driving.

Such classes have the advantage that they are understandable to the driver and they can also be displayed to him.

• – Variieren von Eingriffen in das Fahrwerk des Fahrzeugs und/oder
• – Variieren von Maßnahmen bei einer unvermeidlichen Kollision und/oder
• – Variieren der durch das Fahrerassistenzsystem unterstützten Manöver (Spurwechsel, Überholen, Ausweichen, Kreisverkehr, etc.) und/oder
• – Variierung der Aktionsaufforderungen oder Übernahmeanforderungen für den Fahrer.

Depending on one or more degrees of automation determined in the method, the following can be carried out:

• - Varying interventions in the chassis of the vehicle and / or
• - Varying measures in the event of an unavoidable collision and / or
• - varying the maneuver supported by the driver assistance system (lane change, overtaking, avoiding, roundabout, etc.) and / or
• - Variation of the action requests or takeover requests for the driver.

Furthermore, a sequence (planning) for activating vehicle functions, the z. B. can be performed by the driver or a driver assistance functions in the near future or should be determined. So z. B. action prompts and / or takeover requests as more or less critical signaling or more or less long-term or short-term to the driver of the vehicle.

• – Routenwahl,
• – Optimierung der Ankunftszeit,
• – Optimierung des Energieverbrauchs,
• – Optimierung des Komforts.

In one development of the invention, an advance of a maneuver of the vehicle and / or a displacement of a maneuver of the vehicle occur, depending on one or more assignments. In this case, an at least partially automated maneuver can be performed in a different lane area as z. B. alone would result from the road. Furthermore, time points or locations for performing at least two planned maneuvers and / or the order of at least two maneuvers are changed as a function of at least one or two determined assignments. The optional preferred steps relate in particular to planned maneuvers depending on:

• - route selection,
• - optimization of arrival time,
• - optimization of energy consumption,
• - Optimization of comfort.

In the preferred variant of the method, these maneuvers are varied in terms of time and / or space (as part of a short- to medium-term movement planning) depending on the determined allocations, resulting in an optimized course of the usable degree of automation.

The invention is also applicable to a method or system for maneuvering assistance, in particular for the near future, which is adapted to assist the driver in selecting a vehicle trajectory in which a particular desired, planned, or necessary maneuver with a usable one , in particular optimized, usable degree of automation can be executed.

In one embodiment of the invention, a haptic and / or kinaesthetic signaling to the driver of the vehicle is generated in addition to or instead of an intervention in the chassis of the vehicle and / or a haptic and / or kinaesthetic signaling to the driver of the vehicle varies.

In this case, a necessary or recommended driving action, which can not be carried out sufficiently well automated within the framework of the determined optimized degree of automation, is replaced by a direction-dependent haptic and / or kinaesthetic signaling to the driver of the vehicle. In the method, a plurality of usable degrees of automation or multiple courses of usable degrees of automation, in particular quasi-simultaneously or synchronized, can be determined for two or more vehicles.

Also included within the scope of the invention is computer program product that may be directly loaded into the internal memory of a digital device (including a computing unit) and includes software code portions that perform the steps of any one of the preceding claims when the product is run on the digital device. A digital device may preferably be an electronic control unit of a driver assistance system in the ego vehicle.

The scope of the invention also includes a device within the vehicle for determining the degree of automation of an at least partially automated movement of a vehicle, comprising means for wireless reception of the first data and / or the second data and a computing unit which is used to determine the second data and / or for determining at least one usable degree of automation of an at least partially automated movement of a vehicle for at least one defined time interval and / or for at least one relevant for the movement of the vehicle lane area is provided. The device can also be configured with means for sending a request, in particular to a device outside the vehicle, wherein the request represents the transmission request of the external data of the external sensor system to be provided.

The scope of the invention also includes a device outside the vehicle, in particular an infrastructure device, comprising an external sensor system mounted substantially above a detection area for carrying out the method or for use in combination with the device within the vehicle, comprising at least one sensor for detection an object constellation and / or a free space area and at least one arithmetic unit for determining the first data representing objects in the detection area of the exterior sensor system and / or the second data, the at least one object constellation and / or a free space area in a specific lane area from the first data represent. Furthermore, the device comprises means for direct or indirect wireless transmission of the first and / or the second data to a vehicle.

Such a device outside the vehicle may be configured as an infrastructure device or may be installed or connected together with an infrastructure device. The device outside the vehicle is in particular configured to carry out or optimize the method according to the invention in combination with the device within the vehicle.

The scope of the invention also includes a vehicle for carrying out the method according to the invention by means of a device discussed above inside the vehicle and / or with a device outside the vehicle discussed above.

The vehicle according to the invention is in particular a motor vehicle. This results in several of the advantages discussed above and others that can be understood by a person skilled in the art. Alternatively or additionally, the method according to the invention can also be applied to watercraft, aircraft and spacecraft or to mobile robots.

The invention is explained below with reference to a drawing in conjunction with exemplary embodiments. It shows

1 1 is a schematic representation of an overall arrangement for carrying out the method according to the invention using the example of a driving range to be traveled by the vehicle in the near future;

2 a course of the usable degree of automation with an assignment to the given classes or category values and

3 a course of the usable degree of automation with respect to several different dimensions or aspects of the automation of the movement of the vehicle.

1 shows a vehicle 1 for which a usable degree of automation or a sequence of several usable degrees of automation or an optimized course of a usable degree of automation for an at least partially automated movement of the vehicle 1 (here the ego vehicle) with an electronic driver assistance unit 2 is determined. In this example, the vehicle is within a defined driving range 3 ( "Roundabout"). A knowledge of the degree of automation that can be used with existing means is for the vehicle 1 , z. B. in a time interval of the next 10-30 sec, without the inventive method not possible.

The substantially above the defined driving range 3 attached device outside the vehicle, in this example an infrastructure device, includes an outdoor sensor 4 , Depending on the first data (here: only slightly preprocessed sensor data, eg image data) from the sensors of the outdoor sensors 4 second data (here: interpreted data representing objects and / or free space areas in one or more of the lane areas) is determined.

The second data is from a transmission module of the external sensor 4 to a receiving module of the vehicle 1 or the driver assistance unit 2 wireless transferable. Alternatively or additionally, the first data become (also) the driver assistance unit 2 transferred and there determines the second data. The first or the second data are transmitted in this example by means of WLAN, LTE or similar data transmission methods or standards. In this case, the driver assistance unit comprises in this case 2 a receiving module for receiving the external sensor data.

In addition, the vehicle has 1 also via an internal vehicle sensor system 7 , The determination of the degree of automation is dependent on the balance of the outdoor sensors 4 dependent received data and the data depending on the vehicle sensors 7 are determined. Thereby a very high confidence of the prediction of the usable automation level within the range 3 reached.

Furthermore, a sequence of automation yams for a plurality of specific roadway areas (or for specific parts of roadway areas) is determined in each case at a plurality of time intervals. Time intervals can also be represented by individual times.

Among other things, probable properties of object constellations and / or free space areas, including their position, are determined at one or more time intervals in the near future. In particular, their respective future position (eg as assignment to specific roadway areas) is determined for these time intervals. In addition to known physical relationships, the probable properties and positions of object constellations and / or free space regions are also used by means of a probability calculation or a simulation.

Several optimized profiles of usable degrees of automation are determined in particular by interpolation of time points or time intervals. Lane areas can be by means of a place representing information, eg. B. more coordinates or other geometric information determined. In particular, lane areas refer to special situations of a route, e.g. As parts of a roundabout, tunnel, construction site, etc., in the example according to 1 the carriageway areas 30 to 34 are defined.

For example, a total of 4 degrees of automation are determined for the time intervals in the next 5 seconds and in the next 20 seconds with respect to two different lanes of the roundabout. According to the invention, knowledge of the available combinations and (also taking into account further criteria mentioned in this application) makes it possible to select the best option for the at least partially automated movement of the vehicle, in particular with regard to an optimized course of the degree of automation according to predetermined criteria.

Several usable degrees of automation for the near future and corresponding assignments can also be determined in the method independently of a specific control task or movement planning of the vehicle. These can affect time intervals, eg. B. 15-120 seconds, relate in the future, for which no regulatory task is yet solvable.

In a further step of the method, a profile of the usable degree of automation is selected according to predetermined criteria, in which no significant change in the degree of automation occurs (or at least no significant decrease) occurs or is required. The motion planning, which underlies the at least partially automated movement of the vehicle in this example, is adapted such that the vehicle 1 certain lane areas, here for example 30 to 34 , reached or occupied at certain time intervals, such that there is an optimized course of the usable degree of automation. In 1 are other objects 11 . 12 and 13 also shown in the determination of the object constellations and / or free space areas in each of the lane areas 30 to 34 can enter.

2 shows a course of the usable degree of automation (here: according to time parameters) with an assignment to the given classes or category values:
A1: "assisted driving",
A2: "semi-automated driving",
A3: "highly automated driving",
A4: "fully automated driving".

The time values t ₁ -t ₄ represent the time intervals for the respective usable degrees of automation (also with reference to the classes A1 to A4) are determined.

If significant anticipated changes in the usable degree of automation in the near future are identified, in particular when changing over to another class, appropriate information is output to the driver. In this example, the driver is signaled at a point in time which is earlier than the change in the usable degree of automation determined by the time interval ΔT. ΔT is a predefined, in particular according to predetermined criteria (eg, size of the change of the degree of automation, driver's condition, etc.) selectable prewarning time.

The first information is output at time t ₃ -ΔT, which is before the drop in the degree of automation determined at the time t ₃ for the near future. This is particularly advantageous because the driver of the vehicle can respond promptly when needed.

In this case, at or before a drop in the degree of automation from A3 to A1 at time t ₃ - ΔT a first information output and at or before an increase in the degree of automation from A1 to A4 at time t ₄ - .DELTA.T issued a second information, wherein the first and the second information qualitatively and / or quantitatively differ. The progression of the degree of automation can also be determined as a spatial progression according to lane areas and, if appropriate, displayed with reference to a symbolic depiction of the vehicle environment (for example, lane area in the surroundings). It is also possible to determine and / or display an assignment of the ascertained degree of automation to an anticipated trajectory or route of the vehicle.

In this example, the method also includes a signaling of the utilized or usable degree of automation of the vehicle 1 to the outside, z. B. to other road users.

• – Längsführung des Fahrzeugs,
• – Querführung des Fahrzeugs,
• – Durchführung eines Spurwechsels,
• – Durchführung eines Überholvorgangs,
• – Fahrerinformation,
• – Signalisierung des Fahrzeugs nach außen.

3 The degree of automation in this example is related to two or more different parameters of the automation and / or two or more different driver assistance functions and / or two or more maneuvers and / or signaling of the vehicle determined externally (separately):

• Longitudinal guidance of the vehicle,
• - transverse guide of the vehicle,
• - Carrying out a lane change,
• - carrying out an overtaking process,
• Driver information,
• - Signaling the vehicle to the outside.

A determined course of the usable degree of automation can also include an assignment to specific classes. In this example, differentiated information related to different aspects of the degree of automation A (a), A (b), A (c) is output to the driver of the vehicle, depending on the various aspects. In this case, the prediction to change specific dimensions or parameters of the degree of automation for the near future to the driver, z. B. by means of a visualized representation transmitted. Thus, the driver can z. B. timely to the fact that its involvement (only) in certain parameters or aspects of vehicle control in the near future will be required.

Also, depending on the determined data, in particular depending on the course of the usable degree of automation at a specific time interval in the near future, the degree of automation may be limited to an earlier time interval, in particular to a lower qualitative or quantitative value. Thus, an unnecessary change in the degree of automation can be avoided or a better course of the degree of automation can be achieved.

• – Ermitteln der Steuerungsdaten für zumindest eine Anzeige innerhalb des Fahrzeugs 1, wobei die Anzeige eine Information, Empfehlung oder Handlungsanweisung für den Fahrer des Fahrzeugs 1 umfasst, die insbesondere eine Bahnführung des Fahrzeugs betrifft, und
• – Ausgabe der Anzeige an den Fahrer des Fahrzeugs, insbesondere wenn die vorausbestimmte Bedingung erfüllt ist.

The useable degree of automation determined in the method, in particular in the form of corresponding spatially responsive (resolved according to certain lane areas) and time-dependent data (resolved after certain time intervals), which represent its course in the near future, can in particular within the vehicle 1 be provided or used differently, for. For example:

• Determining the control data for at least one display within the vehicle 1 wherein the display is an information, recommendation or instruction to the driver of the vehicle 1 comprising, in particular, a web guide of the vehicle, and
• - Output of the display to the driver of the vehicle, especially when the predetermined condition is met.

Such control data may also represent an output of information to the driver as a sequence of a plurality of information to be output, in particular having temporal parameters. Such a sequence may include information transmitted to the driver via two or more different sensing channels in the near future.

• – durch den Aktuator des Fahrzeugs ein vom Fahrer überstimmbares Lenkmoment bewirkt, und/oder
• – durch den Aktuator des Fahrzeugs eine akustische oder haptische Information für den Fahrer erzeugt, die eine Fahrtrichtung oder Manöverrichtung repräsentiert,

wobei die Ansteuerung des Aktuators bevorzugt in einer zeitlichen Abhängigkeit von zumindest einer vorausbestimmten Bedingung erfolgt.Alternatively or additionally, the method in this example comprises a control of at least one actuator of the vehicle 1 as a function of the ascertained usable degree of automation, in particular if, for one or more time intervals, the near future has been determined to be a reduction thereof. For example, it will be there

• - By the actuator of the vehicle causes an over-tunable steering torque by the driver, and / or
• Generates by the actuator of the vehicle an acoustic or haptic information for the driver, which represents a direction of travel or maneuvering,

wherein the actuation of the actuator is preferably carried out in a temporal dependence on at least one predetermined condition.

• – Ermitteln, dass die Fahrerabsicht und die ermittelte optimierte Bewegungsplanung sich im Wesentlichen voneinander unterscheiden und/oder
• – Ermitteln, dass der Fahrer des Fahrzeugs in einer Objektekonstellation ein verdecktes Objekt nicht sehen kann bzw. konnte, und/oder
• – Ermitteln, dass die Ablenkung oder Abwendung des Blicks des Fahrers, insbesondere von einem bestimmten Objekt oder von einer bestimmten Objektekonstellation, einen vorausbestimmten Wert überschreitet.

The corresponding predetermined conditions may be preferred:

• Determining that the driver intention and the determined optimized motion planning essentially differ from one another and / or
• Determining that the driver of the vehicle can not or could not see a hidden object in an object constellation, and / or
• To determine that the distraction or avoidance of the driver's gaze, in particular of a particular object or object constellation, exceeds a predetermined value.

Also, the predetermined condition may be one with means of the vehicle determined state of alertness and / or health of the driver.

In particular, the method can be applied predominantly to certain special parts of a route, which tends to have a particularly low or variable degree of automation. This can be in particular structural special areas of a route, z. As entry or exit to a highway, a maneuvering or turning area, a tunnel, certain areas of an intersection, parking garage exits, etc., or special areas that pose particular risks of overlooking other road users. Thus, the method can improve the progress of the degree of automation within the (much larger) route in a very efficient manner.

QUOTES INCLUDE IN THE DESCRIPTION

This list of the documents listed by the applicant has been 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.

Cited patent literature

• DE 102013205392 A1 [0006]
• DE 102012219574 [0039]

Claims (14)

Method for determining a degree of automation (A1, A2, A3, A4) for an at least partially automated movement of a vehicle ( 1 ) for the near future for at least one particular lane area relevant to the movement of the vehicle ( 30 . 31 . 32 . 33 . 34 ) and / or for at least a specific time interval in the near future, in which first data of an external sensor system ( 4 ) in a coverage area ( 3 ' ) and in which dependent on the first data, second data are determined, which represent at least one object constellation and / or a free space area, and in which from the second data at least one usable for an at least partially automated movement of the vehicle degree of automation (A1, A2 , A3, A4). Method according to claim 1, characterized in that the second data properties of at least one object constellation and / or at least one free space area in the detection area ( 3 ' ) of the external sensor ( 4 ) and / or in the carriageway area ( 3 ). Method according to claim 2, characterized in that the properties of at least one object constellation are determined depending on one or more entries from the following list: position and movement data of an object constellation, shape and / or extent of the object constellation, position of the objects, an object constellation form, relative to one another, relative motion data of the objects forming an object constellation to each other or to a predefined geometric point of the object constellation, object class of the objects which form an object constellation, information representing a shape stability or shape change of the object constellation. Method according to one of the preceding claims, characterized in that the properties of at least one free space area are determined depending on one or more entries from the following list: - shape and / or extent of the free space area, - position and movement data of a free space area, in particular the boundaries of the free space area, - Information that represents a dimensional stability or shape change of the free space area. Method according to one of the preceding claims, wherein two or more possible degrees of automation, which relate to at least two at least partially different lane areas and / or at least two at least partially different time intervals are determined, wherein depending on the determined degrees of automation and / or according to predetermined criteria at least one optimized combination of at least one lane area and at least one time interval is determined. Method according to one of the preceding claims, characterized in that the specific roadway area which is relevant for the movement of the vehicle is a roadway area to be traveled in the near future ( 31 . 32 . 33 . 34 ) or a lane area in which a specific maneuver can or should be performed in the near future, the information representing the lane area to be traveled and / or the maneuver being dependent on a determined driver intention and / or the evaluation of the current one Traffic situation and / or from the route planning of the vehicle is determined. Method according to one of the preceding claims, characterized in that the first data and / or the second data are provided to a lane area which at least partially reflects the particular lane area relevant to the movement of the vehicle ( 31 . 32 . 33 . 34 ) overlaps and / or lies at least partially with respect to the direction of travel of the vehicle in front of such a road area. Method according to one of the preceding claims, characterized in that at least one degree of automation (A1, A2, A3, A4) also depends on the data of an internal vehicle sensor system ( 7 ) is determined. Method according to one of the preceding claims, characterized in that a determined usable degree of automation is assigned to one of a plurality of predetermined classes (A1, A2, A3, A4), each of which presupposes a certain degree of driver involvement in partially automated driving. Method according to one of the preceding claims, characterized in that, depending on a determined change in the usable degree of automation in the near future or in a certain relevant lane area, the following is carried out: - an information to the driver is output and / or - the current movement of the vehicle is changed and / or - a motion planning for the near future is determined or changed and / or - A maneuver planning for a vehicle is determined or changed. Computer program product that directly enters the internal memory of a digital device ( 2 ) and includes software code portions that perform the steps of any one of the preceding claims when the product is stored on the digital device (Fig. 2 ) running. Device inside the vehicle ( 1 ) for determining the usable degree of automation (A1, A2, A3, A4) of an at least partially automated movement of the vehicle ( 1 ), comprising means for receiving the first data and / or the second data in a wireless manner and a computing unit for determining the second data and / or determining at least one usable degree of automation (A1, A2, A3, A4) of an at least partially automated movement of the Vehicle ( 1 ) for at least one defined time interval and / or for at least one lane area relevant to the movement of the vehicle ( 30 . 31 . 32 . 33 . 34 ), wherein the first data depends on a substantially above the detection range ( 3 ' ) and at least almost statically mounted external sensors ( 4 ), wherein the second data represent at least one object constellation and / or at least one free space area. Device outside the vehicle ( 1 ) and outside of another vehicle, in particular an infrastructure device, comprising a substantially above a detection area ( 3 ' ) mounted external sensors ( 4 ) for performing the method and / or for use in combination with the device according to the preceding claim, comprising at least one sensor for detecting an object constellation and / or a free space area and at least one arithmetic unit for determining the first data, the objects in the detection area ( 3 ' ) of the external sensor ( 4 ), and / or the second data representing at least one object constellation and / or a free space area, from the first data, further comprising means for directly or indirectly wirelessly transmitting the first and / or the second data to a vehicle. Vehicle ( 1 ) for carrying out the method according to one of claims 1 to 10 by means of a device according to at least one of claims 12 or 13.

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