Patent Description:
Vehicles are increasingly provided with autonomous driving capabilities which at present are provided by advanced driving assistance systems (ADAS) and only cover particular operational contexts, i.e. traffic situations, of the vehicles (levels <NUM> and <NUM>). However, fully autonomous vehicles (level <NUM>) are expected to be available in the future which are operated basically without any intervention of a driver.

An autonomous driving functionality of a vehicle is, on the one hand, based on a digital environmental model of the vehicle. The digital environmental model comprises object data being related to one or more objects in a detection environment of the vehicle. The detection environment is defined by an area surrounding the vehicle and within ranges of environmental sensors of the vehicle.

On the other hand, the autonomous driving functionality may rely on external data like traffic data, weather data, construction site data and the like. Therefore, many vehicles have radio interface units for connecting to a radio access network (RAN) over the air (OTA), i.e. via a wireless connection. While traffic data, weather data, construction site data and the like will mostly not be time-critical, trajectory data, i.e. positions, velocities, accelerations, of vehicles involved in the same operational context, however, certainly is time-critical. Thus, autonomous driving functionalities relying on operational context data, i.e. adaptive cruise control (ACC) systems and the like, require external data in real time. As a consequence, the radio access network has to allocate a minimum data rate and/or a maximum latency to the wireless connection.

A list of items connected by "and/or" is to be understood as "at least one of" the listed items throughout the application.

The external data may also comprise a high definition map. <CIT> discloses a method for updating an interoperable high definition map. A central server updates a tile of the interoperable high definition map with object data sensorially detected by vehicles in their respective environments and wirelessly provided to the central server by the vehicles. The vehicles are operated using the updated interoperable high definition map wirelessly provided by the central server.

<CIT> discloses a method for controlling an autonomous vehicle. The method provides the autonomous vehicle with object data being sensorially detected or wirelessly received and concerning an environment of the autonomous vehicle. The autonomous vehicle adaptively maintains a distance from both a preceding and a following further vehicle using the provided object data.

Traffic situations may comprise a plurality of vehicles which have different detection environments and, hence, use different digital environmental models. Some vehicles have a small detection environment while other vehicles have a large detection environment. Digital environmental models of the former vehicles comprise less object data than digital environmental models of the latter vehicles. Thereby, the terms « large » and « small » shall be understood not only spatial, i.e. indicating a size of the detection environment, but also qualitative, i.e. indicating an amount or a precision of data.

As a result, the vehicles having a poorer digital environmental model covering a smaller detection environment are operated less safely than the vehicles having a richer digital environmental model comprising a larger detection environment. Consequently, vehicles having a poorer digital environmental model may easily impact a safe operation of vehicles having a richer digital environmental model, particularly in complex traffic situations comprising a high spatial density of a plurality of vehicles.

Hence, it would be desirable to increase an operational safety of vehicles being involved in complex traffic situations.

Therefore, it is an object of the present invention to propose a method for operating a vehicle which generally and particularly in complex traffic situations provides a safe operation of the vehicle. Another object of the invention is a computer program product for safely operating a vehicle.

One aspect of the invention is a method wherein a vehicle is operated according to claim <NUM>.

In many embodiments, the positional data and the object data is detected and provided by at least one environmental sensor of the vehicle, the at least one environmental sensor defining the detection environment of the vehicle to be a union of detection areas of respective environmental sensors of the vehicle. The at least one environmental sensor may comprise a camera, a RADAR sensor, a LIDAR sensor, an ultrasonic sensor and the like. Furthermore the at least one environmental sensor may comprise a GPS antenna for providing the vehicle with positional data.

In other embodiments, the vehicle merges the detected object data and the virtual object data for generating the extended digital environmental model. The merging is done by the electronic control unit of the vehicle which reduces a load of the edge data center.

The edge data center may provide and execute a dedicated application for each connected vehicle, the dedicated applications exchanging detected object data via APIs (Application Programming Interface). The application architecture is flat, but may require the edge data center to simultaneously execute a plurality of equal dedicated applications exchanging object data with each other. The application architecture may be readily parallelized, i.e. simultaneously executed by a plurality of processors.

The merging is done by the edge data center which reduces a load of the electronic control unit of the vehicle.

The edge data center may provide and execute a single common application for all connected vehicles and an extension application, the common application forwarding each received digital environmental model to the extension application, the extension application generating and returning the extended digital environmental model to the common application. The application architecture is hierarchical and simple and requires the edge data center to simultaneously execute only two applications exchanging object data with each other.

The edge data center is preferably provided with an environmental model of at least one further vehicle, the detection environment of the at least one further vehicle spatially overlapping with the virtual environment of the vehicle and comprising the virtual object data. Due to the overlapping objects detected by the further vehicle may be virtual objects for the vehicle.

Most preferably, the edge data center is provided with respective digital environmental models of a plurality of further vehicles. The more further vehicles provide a digital environmental model the larger may the virtual environment be and, hence, the richer may the extended digital environmental model be.

In another embodiment, the edge data center matches digital environmental models of spatially overlapping detection environments and/or checks a plausibility of digital environmental models of spatially overlapping detection environments. The edge data center, thus, may apply corrections to the digital environmental models regarding the comprised object data. For instance, differing positional data of the same object detected by different vehicles may be averaged in order to obtain unique positional data. The edge data center also may eliminate a multiplicity of object data in order to only keep one instance of each object data. Furthermore, the edge data center may identify and correct any erroneous object data which may be provided by a defective environmental sensor.

In an embodiment, the edge data center updates detected object data and virtual object data dependent on a trajectory of the respective vehicle and/or a respective detected object. The trajectory comprises a position of the vehicle, a direction of the vehicle, a velocity of the vehicle and/or an acceleration of the vehicle. Updating the detected object data comprises advancing the detected object data on a time scale in order to prevent the object data from being outdated and obsolete.

In an embodiment, the cellular network allocates a predetermined combination of a minimum data rate and/or a maximum latency for uplink and downlink, respectively, to the wireless connection. A specification of a radio communication protocol may define a plurality of predetermined combinations of minimum data rate values and maximum latency values. The combinations may cover a range from a practical non-availability to an ideal availability of the data rate and/or latency and may prefer either the data rate or the latency between the non-availability and the ideal availability.

In an embodiment, the edge data center advantageously updates the detected object data and the virtual object data dependent on an uplink latency of the wireless connection and a run time within the cellular network. According to the invention, the edge data center transposes the additional object data into the future dependent on a downlink latency of the wireless connection and a run time within the cellular network. Updating the detected object data comprises forecasting the object data in order to compensate for delays caused by the cellular network. Due to the allocation of the minimum data rate and/or the maximum latency to the wireless communication a possible delay caused by the wireless connection is known to the edge data center.

In an embodiment, the extended digital environmental model is updated periodically or event-driven. Periodic updating ensures the extended digital environmental model to be always up to date. However, there might be superfluous updates. For instance, a traffic situation of vehicles waiting at a red traffic light does not change over a predetermined time. Event-driven updating avoids unnecessary updates, but may fail to always keep the digital environmental model up to date. This case may occur when an event requiring an update is missed. Eventually, periodic updates and event-driven updates may be advantageously combined.

Another aspect of the invention is a computer program product for operating a vehicle, according to claim <NUM>.

An essential advantage of the inventive method is that a vehicle originally having a small detection environment is provided with a digital environmental model corresponding to a large detection environment. Thus, an operational safety of the vehicle is increased. In a complex traffic situation comprising the vehicle and further vehicles, the further vehicles are operated also more safely as a consequence. Therefore, an accident risk of the complex traffic situation is reduced.

Further advantages and configurations of the invention become apparent from the following description and the enclosed drawings.

The invention is described in detail by means of an exemplary embodiment and with reference to the drawings.

<FIG> schematically shows a structural diagram of a radio access network <NUM> according to an embodiment of the invention. The radio access network <NUM> comprises a plurality of access nodes <NUM>, <NUM> with the access node <NUM> being configured as a base station of a cellular communication network and the access node <NUM> being configured as a W-LAN router. Each access node <NUM>, <NUM> supports corresponding wireless connections <NUM>, <NUM>, the wireless connection <NUM> being configured according to a standardized radio technology, i.e. LTE, <NUM>, a previous or a future radio technology standard and the wireless connection <NUM> being configured according to the standard IEEE <NUM> family.

Furthermore, the radio access network <NUM> comprises a plurality of edge data centers <NUM> and a backbone having a plurality of stationary backbone nodes <NUM>. The stationary backbone nodes <NUM> are not qualified in detail for avoiding any confusion as they are not essential for the invention. The random access network <NUM> provides wireless connections to a plurality of user equipment devices <NUM>, the wireless connections allowing the user equipment devices <NUM> to access an internet <NUM> which is symbolized as a cloud.

The radio access network <NUM> and the user equipment device <NUM> comprise a program code of a computer program product according to the invention. The program code is executed by a processor of a user equipment device <NUM> and/or by a processor of a stationary network node of the radio access network <NUM>.

<FIG> schematically shows a top view of a plurality of vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> being operated in a method according to an embodiment of the invention. The vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> are user equipment devices <NUM> as shown in <FIG>.

Each vehicle <NUM>, <NUM>, <NUM>, <NUM>, <NUM> has a respective detection environment <NUM>, <NUM>, <NUM>, <NUM>, <NUM>. The vehicle <NUM> originally has a small detection environment <NUM> which is additionally illustrated separate for a better overview. Each vehicle <NUM>, <NUM>, <NUM>, <NUM>, <NUM> comprises at least one environmental sensor, a radio interface unit and an electronic control unit being connected to each environmental sensor and the radio interface unit. These components of the vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> are not shown for avoiding any confusion as they are well known.

The vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> are involved in a complex traffic situation <NUM> comprising five vehicles driving on two parallel lanes of a road <NUM> next to each other. In the traffic situation <NUM> the vehicle <NUM> has an extended environment <NUM> which is a union of portions of the detection environments <NUM>, <NUM>, <NUM>, <NUM> overlapping with a virtual environment <NUM> of the vehicle <NUM>.

When there is no overlapping of a detection environment <NUM>, <NUM>, <NUM>, <NUM> with the virtual environment <NUM> of the vehicle <NUM>, i.e. in a simple traffic situation, the vehicle <NUM> is operated using a digital environmental model wherein the digital environmental model comprises object data related to one or more objects detected in the detection environment <NUM> of the vehicle <NUM>. In the illustrated example, only the further vehicles <NUM>, <NUM> would be objects within the detection environment <NUM> of the vehicle <NUM>.

During the operation of the vehicle <NUM>, the vehicle <NUM> provides the edge data center <NUM> of the cellular network <NUM> with positional data of the vehicle <NUM> via a wireless connection <NUM>, <NUM> to the cellular network <NUM>. The cellular network <NUM> allocates a predetermined combination of a minimum data rate and/or a maximum latency for uplink and downlink, respectively, to the wireless connections <NUM>, <NUM>.

The positional data and the object data are detected and provided by at least one environmental sensor of the vehicle <NUM>. The at least one environmental sensor defines the detection environment <NUM> of the vehicle <NUM> to be a union of detection areas of respective environmental sensors of the vehicle <NUM>. The vehicle <NUM> may comprise a camera, a RADAR sensor, a LIDAR sensor, an ultrasonic sensor and/or the like. Furthermore the vehicle <NUM> may comprise a GPS antenna for providing the vehicle with positional data.

The edge data center <NUM> is provided with environmental models of the further vehicles <NUM>, <NUM>, <NUM>, <NUM>. The detection environments <NUM>, <NUM>, <NUM>, <NUM> of the further vehicles <NUM>, <NUM>, <NUM>, <NUM> spatially overlap with the virtual environment <NUM> of the vehicle <NUM> and comprise virtual object data.

Furthermore, the edge data server updates detected object data and virtual object data dependent on a trajectory of the respective vehicle <NUM>, <NUM>, <NUM>, <NUM>, <NUM> and/or a respective detected object. Apart from that, the edge data server updates the detected object data and the virtual object data dependent on an uplink latency of the wireless connection <NUM>, <NUM> and a run time within the cellular network <NUM> and/or transposes the additional object data into the future dependent on a downlink latency of the wireless connection <NUM>, <NUM> and a run time within the cellular network <NUM>.

The edge data center <NUM> provides the vehicle <NUM> with the virtual object data via the wireless connection <NUM>, <NUM>. The edge data center <NUM> determines the virtual environment <NUM> of the vehicle <NUM> to be an environment located according to the provided positional data.

The virtual object data is related to one or more objects in the virtual environment <NUM> of the provided positional data which spatially exceeds the detection environment <NUM> of the vehicle <NUM>.

In one embodiment, the vehicle <NUM>, i.e. the electronic control unit of the vehicle <NUM>, merges the detected object data and the virtual object data for generating an extended digital environmental model. The edge data center <NUM> provides and executes a dedicated application for each connected vehicle <NUM>, <NUM>, <NUM>, <NUM>, <NUM>. The dedicated applications have respective APIs and exchange detected object data via the APIs.

In an alternative embodiment, the vehicle <NUM> provides the edge data center <NUM> with the digital environmental model via the wireless connection <NUM>, <NUM>. The edge data center <NUM> merges the detected object data and the virtual object data for generating the extended digital environmental model. The edge data center <NUM> provides the vehicle <NUM> with the generated extended digital environmental model comprising the virtual object data via the wireless connection <NUM>, <NUM>. The edge data center <NUM> provides and executes a single common application for all connected vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> and an extension application, the common application forwarding each received digital environmental model to the extension application, the extension application generating and returning the extended digital environmental model to the common application.

The edge data center <NUM> matches the digital environmental models of the spatially overlapping detection environments <NUM>, <NUM>, <NUM>, <NUM>, <NUM> and checks a plausibility of the digital environmental models of the spatially overlapping detection environments <NUM>, <NUM>, <NUM>, <NUM>, <NUM>.

The vehicle <NUM> is operated using the extended digital environmental model comprising a union of the detected object data and the virtual object data and covering the extended environment <NUM> of the vehicle <NUM>. The extended environment <NUM> exceeds the detection environment <NUM> of the vehicle <NUM>. The extended environmental model comprises object data related to the further vehicles <NUM> and <NUM>. The extended digital environmental model is updated periodically or event-driven during operation of the vehicle <NUM>.

Claim 1:
A method for operating a vehicle (<NUM>), wherein
- a vehicle (<NUM>) is operated using a digital environmental model, the digital environmental model being defined by at least one environmental sensor of the vehicle (<NUM>) and comprising object data related to one or more objects detected in a detection environment (<NUM>) of the vehicle (<NUM>);
- the vehicle (<NUM>) provides an edge data center (<NUM>) of a cellular network (<NUM>) with positional data of the vehicle (<NUM>) via a wireless connection (<NUM>, <NUM>) to the cellular network (<NUM>);
- the edge data center (<NUM>) provides the vehicle (<NUM>) with virtual object data via the wireless connection (<NUM>, <NUM>), the virtual object data being related to one or more objects in a virtual environment (<NUM>) of the provided positional data which spatially exceeds the detection environment (<NUM>) of the vehicle (<NUM>);
- the vehicle (<NUM>) is operated using an extended digital environmental model comprising a union of the detected object data and the virtual object data and covering an extended environment (<NUM>) of the vehicle (<NUM>), the extended environment (<NUM>) exceeding the detection environment (<NUM>) of the vehicle (<NUM>),
characterised in that the virtual environment (<NUM>) comprises additional objects missing in the detection environment, wherein the edge data center (<NUM>) transposes the additional object data into the future dependent on a downlink latency of the wireless connection (<NUM>, <NUM>) and a runtime within the cellular network (<NUM>);