DE102024201280A1 - Method for at least partially automated driving of a motor vehicle - Google Patents

Abstract

The invention relates to a method for at least partially automated driving of a motor vehicle, comprising the following steps:
Receiving environmental signals that represent the environment of the motor vehicle,
Determining, based on the environmental signals, that a remote map server must be queried for a map section of a digital rail map representing the environment of the motor vehicle,
Sending a request to the remote map server for the map section of the digital rail map,
Receiving a response from the map server to the request,
Generating control signals for at least partially automated control of a lateral and/or longitudinal guidance of the motor vehicle based on the received response,
Output the generated control signals.
The invention relates to a device, a computer program and a machine-readable storage medium.

Description

The invention relates to a method for at least partially automated driving of a motor vehicle, a device, a computer program and a machine-readable storage medium.

State of the art

The disclosure document CN 107 533 630 A discloses a method for collecting data from moving vehicles.

The patent specification US 11,131,550 B2 discloses a method for creating a road map.

The disclosure document US 2021/0063200 A1 discloses a system for creating a map.

Disclosure of the invention

The object underlying the invention is to provide a concept for the efficient, at least partially automated driving of a motor vehicle.

This object is achieved by means of the respective subject matter of the independent claims. Advantageous embodiments of the invention are the subject matter of the respective dependent subclaims.

According to a first aspect, a method for at least partially automated driving of a motor vehicle is provided, comprising the following steps: receiving environmental signals which represent an environment of the motor vehicle,

Determining, based on the environmental signals, that a remote map server must be queried for a map section of a digital rail map representing the environment of the motor vehicle,

Sending a request to the remote map server for the map section of the digital rail map,

Receiving a response from the map server to the request,

Generating control signals for at least partially automated control of a lateral and/or longitudinal guidance of the motor vehicle based on the received response,

Output the generated control signals.

According to a second aspect, a device is provided which is configured to carry out all the steps of the method according to the first aspect.

According to a third aspect, a computer program is provided which comprises instructions which, when the computer program is executed by a computer, for example by the device according to the second aspect, cause the computer to carry out a method according to the first aspect.

According to a fourth aspect, a machine-readable storage medium is provided on which the computer program according to the third aspect is stored.

The invention is based on and incorporates the finding that the above-mentioned object is achieved by the motor vehicle requesting information, the map section, from a digital rail map from a remote map server when needed. This information relates to the surroundings of the motor vehicle. Based on a response from the map server, the motor vehicle is guided at least partially automatically.

When driving a motor vehicle in at least a partially automated manner, it is advantageous to have knowledge of the vehicle's surroundings. This means, for example, that it is advantageous to know which objects are located where in the vehicle's surroundings.

For this purpose, the motor vehicle can, for example, detect its surroundings using its environmental sensors and drive at least partially automatically based on this detection.

However, it may happen that the environmental sensors fail to detect all important objects, i.e., objects relevant for at least partially automated driving. Such objects include, for example, rails or tracks for rail vehicles, which cannot always be detected well by environmental sensors, or in some cases cannot be detected at all.

Information about whether a track or rail is present in the vicinity of a motor vehicle can be important for the at least partially automated driving of a motor vehicle. For example, a motor vehicle should only cross a rail or track at a certain maximum speed. It can also be advantageous for a motor vehicle to decelerate when approaching the rail or track, i.e., reduce its speed, in order to avoid rail vehicles traveling on the track. or driving on the track, in good time using the environmental sensors.

It is therefore advantageous to query the remote map server for information about the vehicle's surroundings from a digital rail map. A digital rail map includes information about tracks or rails for rail vehicles, so the map server can, for example, provide information about whether there are rails or tracks in the vehicle's surroundings.

As a rule, standard digital road maps, such as those used by well-known navigation systems for motor vehicles, do not include such information, so that the motor vehicle cannot obtain this information from such digital road maps.

This advantageously allows the motor vehicle to be efficiently guided, at least partially automatically, in situations where, for example, a road intersects with rails or tracks. In particular, the current situation in which the motor vehicle is located can be better and more efficiently interpreted using the additional information from the map server, allowing the motor vehicle to respond appropriately and optimally to the current situation.

This results in the technical advantage that a concept for the efficient, at least partially automated driving of a motor vehicle is provided.

The term "at least partially automated driving" encompasses one or more of the following cases: assisted driving, partially automated driving, highly automated driving, or fully automated driving. The term "at least partially automated" therefore encompasses one or more of the following cases: assisted, partially automated, highly automated, or fully automated. At least partially automated driving of the motor vehicle encompasses at least partially automated control of the lateral and/or longitudinal guidance of the motor vehicle.

Assisted driving corresponds to automation level 1 according to the definition of the Federal Highway Research Institute (BASt). Partially automated driving corresponds to automation level 2 according to the BASt definition. Highly automated driving corresponds to automation level 3 according to the BASt definition. Fully automated driving corresponds to automation level 4 according to the BASt definition. Autonomous driving corresponds to automation level 5 according to SAE (J3016), where SAE stands for "Society of Automotive Engineers."

Assisted driving means that a driver of a motor vehicle continuously performs either the lateral or longitudinal control of the vehicle. The other driving task (i.e., controlling the longitudinal or lateral control of the vehicle) is performed automatically. This means that with assisted driving, either the lateral or longitudinal control is controlled automatically.

Partially automated guidance means that the longitudinal and lateral guidance of the vehicle is automatically controlled in a specific situation (for example, driving on a highway, driving within a parking lot, overtaking an object, driving within a lane defined by lane markings) and/or for a specific period of time. The driver of the vehicle does not have to manually control the longitudinal and lateral guidance of the vehicle. However, the driver must continuously monitor the automatic control of the longitudinal and lateral guidance in order to intervene manually if necessary. The driver must be ready to fully assume control of the vehicle at any time.

Highly automated guidance means that, for a certain period of time in a specific situation (e.g., driving on a highway, driving within a parking lot, overtaking an object, driving within a lane defined by lane markings), the longitudinal and lateral guidance of the vehicle are automatically controlled. The driver of the vehicle does not have to manually control the longitudinal and lateral guidance of the vehicle. The driver does not have to continuously monitor the automatic control of the longitudinal and lateral guidance in order to intervene manually if necessary. If necessary, a takeover request is automatically issued to the driver to take over control of the longitudinal and lateral guidance, in particular with a sufficient time reserve. The driver must therefore potentially be capable of taking over control of the longitudinal and lateral guidance. Limits of the automatic control of the lateral and longitudinal guidance are automatically detected. With highly automated guidance, it is not possible to automatically bring about a risk-minimal state in every initial situation.

Fully automated guidance means that in a specific situation (for example: driving on a motorway, driving within a parking space, overtaking an object, driving within a lane defined by lane markings) longitudinal and lateral guidance of the motor vehicle are controlled automatically. A driver of the motor vehicle does not have to manually control the longitudinal and lateral guidance of the motor vehicle. The driver does not have to monitor the automatic control of the longitudinal and lateral guidance in order to be able to intervene manually if necessary. Before the automatic control of the lateral and longitudinal guidance is ended, the driver is automatically requested to take over the driving task (controlling the lateral and longitudinal guidance of the motor vehicle), in particular with a sufficient time reserve. If the driver does not take over the driving task, the system automatically returns to a risk-minimal state. Limits of the automatic control of the lateral and longitudinal guidance are automatically detected. In all situations, it is possible to automatically return to a risk-minimal system state.

Autonomous driving means that the longitudinal and lateral guidance of the vehicle is automatically controlled in all situations, not just in one or more specific situations. The driver is no longer required as a fallback. The vehicle can thus drive driverless.

The terms “assist” and “support” can be used synonymously.

The abbreviation “at least one” means “one or more”.

For example, the motor vehicle is designed to be driven at least partially automatically.

In one embodiment of the method, it is provided that the environmental signals are processed in order to detect at least one traffic sign capable of securing a level crossing in the environment of the motor vehicle, wherein the determination is carried out based on a result of the detection.

This provides, for example, the technical advantage of allowing the determination to be carried out efficiently. This embodiment is based on the knowledge that there are traffic signs that are usually located near a railroad crossing and, for example, mark or secure such a crossing.

To verify the plausibility of such a traffic sign, for example, the vehicle can request relevant information about the vehicle's surroundings from the remote map server. This allows, for example, traffic sign recognition to be verified based on the map server's response.

Furthermore, there may be traffic signs that can be located near a railroad crossing to mark and/or secure it. However, such traffic signs can also be located at a different location where there is no railroad crossing. An example of such a traffic sign is a stop sign.

Thus, if a motor vehicle detects such a stop sign using its environmental sensors, it cannot know based on this information alone whether the stop sign is at a normal road intersection or whether it is protecting a railway crossing.

A motor vehicle usually crosses a railway crossing differently than a road intersection, for example at a lower speed, so that when a corresponding traffic sign is detected, in this case for example the stop sign, it is advantageous to query the remote map server for information about the surroundings of the motor vehicle.

In one embodiment of the method, it is provided that the at least one traffic sign is selected from the following group of traffic signs: stop sign, St. Andrew's cross, level crossing, single- or multi-lane beacon, stop sign for rail vehicles.

This provides the technical advantage, for example, that particularly suitable traffic signs can be selected.

In one embodiment of the method, it is provided that if at least one traffic sign capable of securing a level crossing is detected in the vicinity of the motor vehicle, it is determined that a request must be sent to the remote map server for the map section of the digital rail map.

In one embodiment of the method, it is provided that a position of the motor vehicle is determined in a digital road map representing the surroundings of the motor vehicle, wherein the determination is carried out based on the determined position.

This provides the technical advantage, for example, that the determination can be carried out efficiently.

As already mentioned above, digital road maps do not always include information about rails or tracks. However, a digital road map can provide an indication of indicate that a rail or track may be located in the vicinity of the motor vehicle. Such an indication may, for example, indicate that one of the traffic signs described above is located in the vicinity of the motor vehicle. Thus, such a traffic sign can be detected not only based on the surrounding signals, but can also be detected using a digital road map, or instead of it.

In one embodiment of the method, it is provided that if the response comprises a map section of a digital rail map which indicates that there is a level crossing in the vicinity of the motor vehicle, and if the motor vehicle is to cross the level crossing, a maximum speed is specified at which the motor vehicle may cross the level crossing, wherein the control signals are generated based on the specified maximum speed in such a way that the motor vehicle, with at least partially automated control of the lateral and/or longitudinal guidance based on the output control signals, crosses the level crossing at a speed which is less than or equal to the specified maximum speed.

This results in the technical advantage, for example, that the motor vehicle can cross a railway crossing safely. It is advantageous for the motor vehicle to cross a railway crossing at a lower maximum speed than a road crossing, since conventional rail vehicles have a longer braking distance than motor vehicles in typical traffic situations at road intersections. The lower crossing speed results in the technical advantage, for example, that the braking distance for the motor vehicle can be reduced, so that if necessary, for example, when a rail vehicle approaches, the motor vehicle can stop in time before the railway crossing.

The lower crossing speed, for example, results in the technical advantage that more time is available for analyzing the environmental signals or for processing the environmental signals, for example to detect a rail vehicle on the rail or tracks, than with a higher crossing speed.

In one embodiment of the method, it is provided that if the response comprises a map section of a digital rail map which indicates a position of a stop for a rail vehicle, the control signals are generated based on the position of the stop such that the motor vehicle reduces its speed when approaching the position of the stop in an at least partially automated control of the lateral and/or longitudinal guidance based on the output control signals.

This results in the technical advantage, for example, of increasing safety for road users, such as pedestrians waiting at a stop, due to the lower vehicle speed. This effectively reduces the braking distance for the vehicle due to the lower speed, allowing the vehicle to react in time to people quickly crossing the street to get to the stop and reach a rail vehicle in time.

Such information, i.e. information about the position of a stop for a rail vehicle, is usually included in digital rail maps, since the position of the stop is relevant for rail vehicles.

For example, the device is programmed to execute the computer program.

The method is carried out, for example, by means of the device.

For example, the method is a computer-implemented method.

Device features result analogously from corresponding process features, and vice versa. Statements made in connection with the device apply analogously to the process, and vice versa. Technical functionalities of the process result analogously from corresponding technical functionalities of the device, and vice versa.

A digital rail map includes, for example, one or more of the following information: track layout, track layout, position of one or more stops for a rail vehicle, position of a level crossing, position and/or type of a signal, position and/or type of a boundary sign, position and/or type of a switch.

A map section includes, for example, one or more of the following information: track layout, track layout, position of one or more stops for a rail vehicle, position of a level crossing, position and/or type of a signal, position and/or type of a boundary sign, position and/or type of a switch.

The response of the map server includes, for example, a representation of the surroundings of the vehicle. present map section of the digital rail map.

Environmental signals within the meaning of the description include, for example, environmental sensor data from one or more environmental sensors. Environmental sensor data is based on the detection of the surroundings of the motor vehicle by one or more environmental sensors and represents the surroundings of the motor vehicle.

An environmental sensor is, for example, one of the following environmental sensors: radar sensor, LiDAR sensor, ultrasonic sensor, image sensor, in particular image sensor of a video camera, magnetic field sensor and infrared sensor.

An environmental sensor is, for example, an environmental sensor of a motor vehicle.

An environmental sensor is, for example, an environmental sensor of an infrastructure. Such an environmental sensor is located, for example, on the road on which the vehicle is currently traveling.

An environmental sensor can, for example, be an environmental sensor of another motor vehicle.

In other words, the motor vehicle receives information about its surroundings, for example from one or more sources: its own surrounding sensors and/or surrounding sensors from one or more other motor vehicles and/or the infrastructure.

The method comprises, for example, the step of at least partially automated control of the lateral and/or longitudinal guidance of the motor vehicle based on the output control signals.

The device is implemented, for example, as a control unit, in particular as a main control unit, of the motor vehicle.

For example, a motor vehicle is disclosed comprising the device according to the second aspect.

The motor vehicle comprises, for example, one or more environmental sensors which are configured to detect an environment of the motor vehicle and to output environmental sensor data based on the detection.

In one embodiment of the method, this comprises detecting the surroundings of the motor vehicle using one or more surroundings sensors of the motor vehicle in order to output surroundings sensor data based on the detection.

For example, the maximum speed at which a motor vehicle may cross a level crossing is in the closed interval of 5 km/h to 10 km/h.

A road intersection can, for example, be a motor vehicle with a maximum speed of greater than or equal to 10 km/h.

Sending the request to the remote map server includes, for example, sending a request via one or more communication networks, such as a mobile network and/or a WLAN network.

A track, as defined in this description, refers to a trackway for a rail vehicle. A track comprises, in particular, one or two or more rails.

The embodiments and exemplary embodiments described here can be combined with one another in any way, even if this is not explicitly described.

• 1 ein Ablaufdiagramm eines Verfahrens nach dem ersten Aspekt,
• 2 eine Vorrichtung nach dem zweiten Aspekt,
• 3 ein maschinenlesbares Speichermedium nach dem vierten Aspekt,
• 4 - 6 jeweils eine Verkehrssituation,
• 7 eine Draufsicht auf ein schematisch gezeichnetes Schienenfahrzeug und
• 8 ein Kraftfahrzeug vor einem Bahnübergang.

The invention is explained in more detail below using preferred embodiments. These show:

• 1 a flowchart of a method according to the first aspect,
• 2 a device according to the second aspect,
• 3 a machine-readable storage medium according to the fourth aspect,
• 4 - 6 one traffic situation each,
• 7 a plan view of a schematically drawn rail vehicle and
• 8 a motor vehicle in front of a railway crossing.

In the following, the same reference symbols may be used for the same features.

• Empfangen 101 von Umfeldsignalen, welche ein Umfeld des Kraftfahrzeugs repräsentieren,
• Bestimmen 103 basierend auf den Umfeldsignalen, dass ein entfernter Kartenserver nach einem das Umfeld des Kraftfahrzeugs repräsentierenden Kartenausschnitt einer digitalen Schienenkarte angefragt werden muss, Senden 105 einer Anfrage an den entfernten Kartenserver nach dem Kartenausschnitt der digitalen Schienenkarte,
• Empfangen 107 einer Antwort des Kartenservers auf die Anfrage,
• Erzeugen 109 von Steuersignalen zum zumindest teilautomatisierten Steuern einer Quer- und/oder Längsführung des Kraftfahrzeug basierend auf der empfangenen Antwort,
• Ausgeben 111 der erzeugten Steuersignale.

1 shows a flowchart of a method for at least partially automated driving of a motor vehicle, comprising the following steps:

• Receiving 101 environmental signals representing an environment of the motor vehicle,
• Determining 103 based on the environment signals that a remote map server is searching for a vehicle environment representative of the vehicle tive map section of a digital rail map must be requested, sending 105 a request to the remote map server for the map section of the digital rail map,
• Receiving 107 a response from the map server to the request,
• Generating 109 control signals for at least partially automated control of a lateral and/or longitudinal guidance of the motor vehicle based on the received response,
• Output 111 of the generated control signals.

2 shows a device 201 which is configured to carry out all steps of the method according to the first aspect.

The device 201 comprises, for example, an input configured to receive the environmental signals. The device 201 comprises, for example, a processor device, which may, for example, comprise one or more processors, configured to carry out the determining step. For example, the device 201 comprises a communication interface configured to send the request to the remote map server. The communication interface is, for example, a cellular interface or a WLAN interface. For example, the device 201 comprises a plurality of such communication interfaces. The communication interface is, for example, configured to receive the response from the map server.

The processor device is configured, for example, to generate the control signals. Device 201 includes, for example, an output configured to output the generated control signals.

Outputting the generated control signals comprises, for example, outputting the generated control signals to one or more actuators of the motor vehicle and/or to one or more control units of one or more actuators of the motor vehicle.

An actuator is, for example, one of the following actuators: brake, steering, drive.

3 shows a machine-readable storage medium 301 on which a computer program 303 is stored. The computer program 303 comprises instructions which, when executed by a computer, cause the computer program 303 to execute a method according to the first aspect.

4 shows a traffic situation 401, which includes a road 403 and a railroad crossing 405. At the railroad crossing 405, the road 403 and the railroad tracks 407 intersect. The traffic situation was recorded from the perspective of a motor vehicle attempting to cross the railroad crossing 405. Another motor vehicle 409 is approaching this motor vehicle. A St. Andrew's cross 411 is located at the railroad crossing. Furthermore, the railroad crossing 405 is secured by barriers 413.

In the present case, the rails 407 are not detectable or can only be detected with great difficulty by an environment sensor, so that in such a situation no information about the course of the rails is available based on environment detection alone.

However, based on environmental detection, the St. Andrew's cross 411 can be detected, so that the vehicle knows that the motor vehicle is in the vicinity of a railroad crossing. In this case, for example, it is determined that a corresponding request must be sent or made to the remote map server. A response from the map server includes, for example, information about the track layout and the indication that there are tracks in the vicinity of the motor vehicle. Based on this information, the motor vehicle can be guided at least partially automatically, as described by way of example in this description, by generating the control signals and outputting these generated control signals.

5 shows a second traffic situation 501. The second traffic situation includes a road 503 and a railroad crossing 505, which is secured by a stop sign 507. The traffic situation 501 was recorded from the perspective of a motor vehicle attempting to cross the railroad crossing 505. Furthermore, a horizontal St. Andrew's cross 509 is located above the stop sign 507.

Here, too, a traffic situation exists in which the motor vehicle cannot detect the tracks 511 using its environmental sensors, for example, using a camera. However, the stop sign 507 and/or the St. Andrew's cross 509 can be detected using a camera of the motor vehicle, so that in such a situation it is determined or specified that a corresponding request must be sent to the remote map server.

6 shows a third traffic situation 601 comprising a road 603, wherein several tracks 605 are embedded in the road 603. The traffic situation 601 was recorded from the perspective of a motor vehicle traveling on the road 603. In the vicinity of the motor vehicle there are further Motor vehicles which, for the sake of clarity, have not been given their own reference symbol.

For example, the tracks 605 cannot be detected using a camera of the motor vehicle. Next to the road 603 is a stop sign 607 for rail vehicles, which can be detected using an environment sensor, such as a camera, of the motor vehicle. If such a traffic sign is detected, it is determined, for example, that a corresponding request must be sent to the remote map server to obtain further information about the surroundings of the motor vehicle, which cannot be obtained by the environment detection based on the vehicle's own environment sensors.

Thus, based on the detection of the stop sign 607, the motor vehicle knows that there must be rails in its vicinity. The motor vehicle can request the exact position and route from the remote map server.

Furthermore, based on the response, the motor vehicle can learn exactly where the stop for rail vehicles is located and adapt its driving style accordingly, for example by reducing its speed when approaching the stop.

7 shows a plan view of a schematically drawn rail vehicle 701 having a camera 703, which, relative to the direction of travel of the rail vehicle 701, is directed forward toward the rails 705 on which the rail vehicle 701 is currently traveling. A field of view of the camera 703 is identified by reference numeral 707. Track sections located within the field of view 707 of the camera 703 are additionally identified by reference numeral 709.

Thus, when traveling over the tracks 705, the rail vehicle 701 can detect them using the camera 703 and, in combination with a position determination of the rail vehicle, for example, using a satellite-based positioning system, determine a position of the rails 705 or a course of the rails 705. Based on such determined information, a digital rail map can be created, for example, as described above.

8 shows an at least partially automated motor vehicle 801, which is located in front of a railroad crossing 803. The reference numeral 805 points to a section of the rails 705, which may be in the field of view of a motor vehicle camera, but cannot be detected by it, which will be described further below.

The railroad crossing 803 is secured by a stop sign 821. The motor vehicle 801 is traveling on a road 807, wherein the road 807 comprises two lanes 809 and 811, each of the lanes 809, 811 being intended for a direction of travel. A center line 813 separates the two lanes 809, 811. The motor vehicle 801 is traveling in the right lane, i.e., lane 811, relative to the plane of the paper, toward the railroad crossing 803. The direction of travel of the motor vehicle 801 is indicated by an arrow with the reference symbol 815.

The motor vehicle 801 includes a camera 817. A field of view of the camera 817 is identified by the reference numeral 819.

In the direction of travel of motor vehicle 801 and in front of level crossing 803 is stop sign 821, which is detected by camera 817.

The motor vehicle 801 records its surroundings using its camera 817 and records the stop sign 821. The rail section, identified by the reference number 805, is located in the field of view 819 of the camera 817, but cannot be recorded by it.

However, the detection of the stop sign 821 determines that a corresponding request for further information about the surroundings of the motor vehicle 801 must be requested from a remote map server.

This remote map server is implemented, for example, in a cloud infrastructure 823. The schematically illustrated map server is identified by reference numeral 825.

For example, in response to the request from the motor vehicle 801, the map server 825 sends a map section 827 from the digital rail map, which includes, for example, the rail section 815.

Furthermore, it is planned, for example, that the rail vehicle 701, which is in 7 was presented and in 8 is shown again by way of example, sends the information about the course of the rails determined using the camera 703 of the rail vehicle 701 to the map server 825 so that the latter can create a digital rail map based thereon.

The concept described here is based on the use of digital rail maps to provide information about the real world and help at least partially automated vehicles behave better. It may happen that rails are not fully visible through a vehicle camera or cannot be clearly detected on a wet road.

For example, railway tracks can be protected by a stop sign. The motor vehicle should behave differently than at a two-road intersection. At a two-road intersection, for example, the motor vehicle can increase speed and travel at 5 km/h to 10 km/h. At a road-rail intersection, it is more advantageous for the motor vehicle to travel at 5 km/h to 10 km/h.

The digital rail map can show the motor vehicle the locations of the tracks and stops, especially stops without shelter, in order to prevent pedestrians from taking action in the first place.

In a city, the digital rail map can help the at least partially automated vehicle transition to a lane with rails, ensuring a smooth transition and avoiding passenger disturbance. Another use of the digital rail map, for example, is to inform the vehicle where the actual rails are located if the vehicle mistakenly detects them as lane markings using its environmental sensors.

In some scenarios, the rails are located on a bridge over the road. Using GPS data, the train traveling on the respective rails can send information about the height of the rails to the map server, which can then create the digital rail map or update an existing one. The backend can then, for example, decide that a bridge is located over the road. This information is important for at least partially automated vehicles, as they may not have GPS reception under a bridge, which can lead to data collected by the vehicle being discarded.

For example, the camera of the rail vehicle can be used to detect landmarks for motor vehicles in order to ensure the consistency of an already created digital road map and to perform a double check for this map.

At least partially automated motor vehicles, for example, are equipped with video or image sensors (cameras) to capture their surroundings. The camera captures an image and, in parallel, triggers various tasks to understand the scene (optical flow, structure from motion, classical computer vision, machine learning). The results of the algorithms are used, for example, to ensure the safety of passengers and elements outside the vehicle (e.g., pedestrians, other vehicles, urban infrastructure). Like motor vehicles, trams and trains, and rail vehicles in general, can also be equipped with a video sensor to ensure safety.

For at least partially automated driving, a digital road map is advantageous, helping motor vehicles locate themselves and obtain information about their surroundings. This can be efficiently supported by a digital rail map, allowing the behavior of motor vehicles to be improved in certain situations. For example, the motor vehicle can cross railway tracks at an appropriate speed.

A landmark, for example, is a permanent, static object such as lane markings, rails, traffic signs, traffic lights, road arrows, and guardrails. A parked motor vehicle is not a landmark because it can move from one moment to the next.

An at least partially automated motor vehicle is particularly capable of recognizing several things: lane markings, road signs, poles, traffic lights, pedestrians, and motor vehicles. These landmarks can be used to create a high-resolution digital road map. For this purpose, motor vehicles, for example, are equipped with a GPS sensor, commonly known as a position sensor, which determines the position of the recognized landmarks in the real world. In rail vehicles, similar to motor vehicles, landmarks can be recognized using an environmental sensor, such as a camera.

A rail vehicle can thus detect the rails or track it is traveling on, as well as other objects such as traffic signs, guardrails, or traffic lights. After the rail vehicle has traveled through a section of track, it can, for example, send the collected data to the map server so that it can create or update a digital rail map.

Commonalities between digital road and digital rail maps can help motor vehicles to ensure consistency of landmarks (road signs, traffic lights, masts).

The rail vehicle detects the rails and models them, for example, using splines. After passing a section of the rails, the data (including the GPS position) is sent to an over-the-air ECU (Electronic Control Unit), which is responsible for communication with the map server. The ECU sends the information to the map server, which further processes this data and, for example, incorporates it into an already created digital rail map.

For example, a motor vehicle near a railroad crossing detects a stop sign at the crossing and queries the map server for the scenario-specific data. The same applies if a tram sends information about tracks to the map server, and the motor vehicle retrieves this information for a lane change, especially if the motor vehicle's camera does not detect the tracks.

The motor vehicle can request information from the digital rail map from the map server based on its own position.

A digital rail map and/or a digital road map can be created or updated based on information gathered from multiple journeys by one or more rail vehicles and/or from multiple journeys by one or more motor vehicles. Such a process can be referred to as a crowdsourcing process. The entire process includes, for example, motor vehicles, rail vehicles, each equipped with video sensor(s), a position sensor, particularly a GPS sensor, precise localization, over-the-air communication, data collection, and averaging in the backend, i.e., the map server.

QUOTES CONTAINED IN THE DESCRIPTION

This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This 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

• CN 107 533 630 A [0002]
• US 11,131,550 B2 [0003]
• US 2021/0063200 A1 [0004]

Claims (9)

A method for at least partially automated driving of a motor vehicle (801), comprising the following steps: Receiving (101) environmental signals representing the environment of the motor vehicle (801); Determining (103) based on the environmental signals that a remote map server must be requested for a map section of a digital rail map representing the environment of the motor vehicle (801); Sending (105) a request to the remote map server for the map section of the digital rail map; Receiving (107) a response from the map server to the request; Generating (109) control signals for at least partially automated control of lateral and/or longitudinal guidance of the motor vehicle (801) based on the received response; Outputting (111) the generated control signals. Procedure according to Claim 1 , wherein the environmental signals are processed in order to detect at least one traffic sign (411, 507, 509, 607) capable of securing a level crossing (405, 505, 803) in the environment of the motor vehicle (801), wherein the determination is carried out based on a result of the detection. Procedure according to Claim 2 , wherein the at least one traffic sign (411, 507, 509, 607) is selected from the following group of traffic signs (411, 507, 509, 607): stop sign (503), St. Andrew's cross (411, 509), level crossing (405, 505, 803), single- or multi-lane beacon, stop sign (607) for rail vehicles (701). Method according to one of the preceding claims, wherein a position of the motor vehicle (801) is determined in a digital road map representing the surroundings of the motor vehicle (801), wherein the determination is carried out based on the determined position. Method according to one of the preceding claims, wherein, if the response comprises a map section of a digital rail map which indicates that a level crossing (405, 505, 803) is located in the vicinity of the motor vehicle (801), and if the motor vehicle (801) is to cross the level crossing (405, 505, 803), a maximum speed is specified at which the motor vehicle (801) may cross the level crossing (405, 505, 803), wherein the control signals are generated based on the specified maximum speed such that the motor vehicle (801), with at least partially automated control of the lateral and/or longitudinal guidance based on the output control signals, crosses the level crossing (405, 505, 803) at a speed which is less than or equal to the specified maximum speed. Method according to one of the preceding claims, wherein, if the response comprises a map section of a digital rail map which indicates a position of a stop for a rail vehicle (701), the control signals are generated based on the position of the stop such that the motor vehicle (801) reduces its speed when approaching the position of the stop in an at least partially automated control of the lateral and/or longitudinal guidance based on the output control signals. Device (201) which is arranged to carry out all steps of the method according to one of the preceding claims. Computer program (303) comprising instructions which, when the computer program (303) is executed by a computer, cause the computer to carry out a method according to one of the Claims 1 until 6 to execute. Machine-readable storage medium (301) on which the computer program (303) according to Claim 8 is stored.