DE102020214745A1 - Improved driving tube - Google Patents

Abstract

The invention relates to a module (10) for determining a corrected driving path (36) for an automatic distance control system (20) of an at least partially assisted driving motor vehicle (24), a motor vehicle (24), a system (22), a method and a corresponding computer program. Provision is made for an ego position of a vehicle (24) to be recorded using a GPS position, camera images and/or swarm data. For example, lanes are determined from the swarm data by means of a frequency distribution. This information is included in the creation of the ACC driving path (32), so that there is a higher probability that a relevant vehicle (34) driving ahead can be selected and adjusted. Misinterpretations are significantly reduced.

Description

The invention relates to a module for determining a corrected driving path for an automatic distance control system of an at least partially assisted driving motor vehicle, a motor vehicle, a system, a method and a corresponding computer program.

It is known to use an automatic distance control system in current motor vehicles. The position and speed of the vehicle in front is determined using a sensor, and the speed and distance of the vehicle behind that is equipped with this system is adaptively controlled with engine and brake intervention. In current production vehicles, among other things, control objects of the ACC (Adaptive Cruise Control) are determined as a function of what is known as a “driving path”. This driving path represents an estimate of the path that will be driven in the future. If objects are detected within this driving path, for example by radar sensors, lidar sensors and/or a camera, these objects are used as active control objects for the automatic distance control system. If an object falls out of this driving path, this object is seen as a no longer active control object for the automatic distance control. For example, there may be situations in the city or on tight bends where the steering wheel has to be turned sharply (this explains the driving tube). In these situations, the driving path is aligned according to the steering wheel angle, with an actually existing and rule-relevant vehicle sometimes no longer being in the driving path. The automatic distance control system, ie the ACC system, would accelerate to a preset set speed and your own motor vehicle would drive into the vehicle in front, which was not recognized as a control object, unhindered.

The invention is now based on the object of creating a possibility of providing an improved driving path for an automatic distance control system. In particular, a realistic driving path should be determined that takes into account all available lanes and minimizes misinterpretations.

• - einer Eingangsschnittstelle zum Empfangen von Eingangsdaten umfassend Sensordaten eines Sensors des Kraftfahrzuges und Schwarmdaten mit Informationen zu einem Fahrbahnabschnitt einer Fahrbahn vor dem Kraftfahrzeug;
• - einer Analyseeinheit zum Bestimmen einer Prädiktion für den Fahrschlauch basierend auf den Sensordaten;
• - einer Ausgangsschnittstelle zum Übermitteln von Informationen bezüglich des Fahrschlauchs, wobei

die Eingangsdaten Schwarmdaten aus einem Schwarmdaten-Pool mit Informationen von Schwarm-Kraftfahrzeugen umfassen und die Analyseeinheit dazu ausgebildet ist, basierend auf der Prädiktion für den Fahrschlauch und den Schwarmdaten den korrigierten Fahrschlauch zu bestimmen.This object is achieved by a module for determining a corrected driving path for an automatic distance control system of an at least partially assisted driving motor vehicle with:

• - An input interface for receiving input data comprising sensor data from a sensor of the motor vehicle and swarm data with information about a roadway section of a roadway in front of the motor vehicle;
• - an analysis unit for determining a prediction for the driving path based on the sensor data;
• - an output interface for transmitting information relating to the driving path, wherein

the input data include swarm data from a swarm data pool with information from swarm motor vehicles and the analysis unit is designed to determine the corrected driving path based on the prediction for the driving path and the swarm data.

• - einem Modul wie zuvor definiert;
• - einem automatischen Abstands-Regelautomaten; und
• - einem Sensor zum Erfassen von Sensordaten mit Informationen bezüglich des Kraftfahrzeugs.

The above object is also achieved by a motor vehicle with:

• - a module as previously defined;
• - an automatic distance control machine; and
• - A sensor for acquiring sensor data with information relating to the motor vehicle.

• einem Kraftfahrzeug wie zuvor definiert und einem Schwarmdaten-Pool, umfassend Schwarmdaten, wobei das System dazu ausgebildet ist, Schwarmdaten mit dem Schwarmdaten-Pool auszutauschen.

The above task is further solved by a system for determining a corrected driving path with:

• a motor vehicle as defined above and a swarm data pool comprising swarm data, the system being designed to exchange swarm data with the swarm data pool.

• - Empfangen von Eingangsdaten, umfassend Sensordaten eines Sensors des Kraftfahrzuges und Schwarmdaten mit Informationen zu einem Fahrbahnabschnitt einer Fahrbahn vor dem Kraftfahrzeug, wobei das Empfangen von Eingangsdaten ein Empfangen von Schwarmdaten aus einem Schwarmdaten-Pool mit Informationen von Schwarm-Kraftfahrzeugen umfasst;
• - Bestimmen einer Prädiktion für den Fahrschlauch basierend auf den Sensordaten;
• - Bestimmen des korrigierten Fahrschlauchs basierend auf der Prädiktion für den Fahrschlauch und den Schwarmdaten;
• - Übermitteln von Informationen bezüglich des korrigierten Fahrschlauchs.

In addition, the above object is achieved by a method for determining a corrected driving path for an automatic distance control system of an at least partially assisted driving motor vehicle, comprising the steps:

• - Receiving input data, comprising sensor data from a sensor of the motor vehicle and swarm data with information about a roadway section of a roadway in front of the motor vehicle, the receiving of input data comprising receiving swarm data from a swarm data pool with information from swarm motor vehicles;
• - determining a prediction for the travel path based on the sensor data;
• - determining the corrected driving path based on the prediction for the driving path and the swarm data;
• - Transmission of information regarding the corrected driving path.

The above object is also achieved by a computer program with program code means in order to carry out all the steps of a method as defined above when the computer program is executed on a computer or a corresponding computing unit.

The use of swarm data can reliably improve the quality of the driving path. First, a driving path can be determined using sensor data from the sensors of the motor vehicle. These sensors have a predefined viewing angle or detection area. By using swarm data, information outside the detection area can be used to improve the driving path. In particular, since swarm data can include data from swarm motor vehicles that have already completely driven through the roadway section of the roadway in front of the motor vehicle and have collected and shared corresponding information about the roadway section. For example, the ego position, ie the actual position, of the motor vehicle can be recorded using a GPS position, camera images and/or the swarm data. Lanes on the roadway section of the roadway in front of the motor vehicle are determined from the swarm data, for example by means of a frequency distribution. This information can flow into the determination of a new driving path and/or modification of a driving path that has already been determined, so that the relevant vehicle driving ahead can be recognized and selected as control objects with a higher probability. Misinterpretations can be significantly reduced.

In a preferred embodiment of the invention, it is provided that the swarm data includes information regarding a trajectory of a swarm motor vehicle on the road section and/or a frequency distribution of the swarm motor vehicles on the road section. As a result, the lanes of the road section can be determined in a technically simple and reliable manner. It goes without saying that the swarm data can also already be pre-processed. For example, information regarding the individual lane can already be stored in the swarm data. Furthermore, a course of the roadway section can be inferred.

Another preferred embodiment of the invention provides that the analysis unit is designed to determine a number of lanes and a course of the lanes on the roadway section based on the trajectory of a swarm motor vehicle and/or a frequency distribution of the swarm motor vehicles. As a result, a number of lanes can be determined in a technically simple and, in particular, fast manner. Using the trajectory and current sensor data, for example from a GPS sensor, the further course of the road section can be predicted in a technically simple and reliable manner. There is a sort of sensor data fusion between swarm data and the sensor data of the motor vehicle.

Another preferred embodiment of the invention provides that the sensor data includes information about a position, a speed, a steering wheel angle and/or a yaw rate of the motor vehicle and/or about a position, a speed and/or a yaw rate of objects on the roadway section. The driving path can be determined more precisely by detecting the position, the speed, the steering wheel angle and/or the yaw rate of one's own motor vehicle. Furthermore, a trajectory of the additional vehicle can be determined by detecting these attributes for an additional vehicle. The driving path can be modified in this way. For example, it can be taken into account if the trajectories of one's own vehicle and the other vehicle overlap and/or fall below a predefined minimum distance. The modified driving path can preferably include all relevant control objects.

In a further preferred embodiment of the invention, it is provided that the analysis unit is designed to determine a corrected driving path based on a weighting of individual pieces of information. As a result, the quality of the corrected driving path can be further improved. In particular, it is conceivable that a weighting is carried out based on a sensor data quality and/or swarm data quality. As a result, malfunctions of individual sensors can be compensated for in a robust manner and preferably do not lead to any impairment of the driving path.

In another preferred embodiment of the invention, it is provided that the module, preferably the output interface of the module, is designed to transmit sensor data from the motor vehicle to the swarm data pool. As a result, a constantly growing swarm data pool can be created. The determination of the driving path can be continuously refined. In addition, changing roadway properties, such as a changed course of the roadway or the blocking of individual lanes, can be taken into account. The swarm data in the swarm data pool can therefore preferably be kept up-to-date at all times.

Further preferred configurations of the invention result from the remaining features mentioned in the dependent claims.

Unless stated otherwise in the individual case, the various embodiments of the invention mentioned in this application can advantageously be combined with one another.

An automatic distance control system, distance control cruise control or an ACC device is a speed control system in motor vehicles that includes the distance to a vehicle driving ahead as an additional feedback and control variable when controlling. The adaptive cruise control is one of the driver assistance systems. In the international automotive industry, the English term Adaptive Cruise Control (ACC) has established itself (in German: adaptive cruise control). The system is also referred to as automatic distance control (ADR), although other names may spread, as car manufacturers like to name their systems individually in order to better distinguish themselves. The system is often part of a radar-based emergency brake assistant and is equipped with a stop-and-go function in some cars.

The driving path is the area in which the objects that can be detected by sensors and are used for regulation, in particular vehicles, are used for distance regulation. It is defined in particular by its width, which can roughly correspond to the lane width. A vehicle consequently moves in a driving envelope that has a specific width and a route that can be calculated.

• 1 eine schematische Darstellung eines erfindungsgemäßen Moduls;
• 2 eine schematische Darstellung eines Moduls, eines Schwarmdaten-Pools und eines automatischen Abstands-Regelautomaten;
• 3 eine schematische Darstellung eines erfindungsgemäßen Systems umfassend ein Kraftfahrzeug und einen Schwarmdaten-Pool;
• 4 eine schematische Darstellung eines Fahrschlauchs bei einer Fahrt;
• 5 eine schematische Darstellung eines korrigierten Fahrschlauchs bei einer Fahrt;
• 6 eine schematische Darstellung einer Bestimmung eines korrigierten Fahrschlauchs; und
• 7 schematisch die Schritte eines erfindungsgemäßen Verfahrens.

The invention is explained below in exemplary embodiments with reference to the associated drawings. Show it:

• 1 a schematic representation of a module according to the invention;
• 2 a schematic representation of a module, a swarm data pool and an automatic distance control machine;
• 3 a schematic representation of a system according to the invention comprising a motor vehicle and a swarm data pool;
• 4 a schematic representation of a driving path during a trip;
• 5 a schematic representation of a corrected driving path during a trip;
• 6 a schematic representation of a determination of a corrected driving path; and
• 7 schematically shows the steps of a method according to the invention.

1 shows a schematic representation of a module 10 for determining a corrected driving path for an automatic distance control system (not shown) of an at least partially assisted driving motor vehicle. The module 10 comprises an input interface 12, an analysis unit 14 and an output interface 16.

The input interface 12 is designed to receive input data. The input data can include sensor data from a sensor of the motor vehicle and swarm data with information about a roadway section of a roadway in front of the motor vehicle. The swarm data comes from a swarm data pool and includes information from swarm motor vehicles.

Analysis unit 14 is designed to determine a prediction for the driving path based on the sensor data. Analysis unit 14 can determine a corrected driving path based on the prediction for the driving path and the swarm data.

The output interface 16 is designed to transmit information relating to the driving path. In addition, the output interface 16 can transmit information relating to a corrected driving path to the automatic distance control system.

It goes without saying that the input interface 12 and the output interface 16 can be combined to form a single interface. It is also understood that the interfaces 12, 16 can be both wireless and wired. In particular, the interfaces 12, 16 can also be designed as software interfaces.

2 shows schematically a module 10, a swarm data pool 18 and an automatic distance control device 20. The same reference symbols refer to the same features and are not explained again.

The swarm data pool 18 includes a large number of swarm data with information from at least one sensor of a swarm motor vehicle. In particular, the swarm data can include information relating to a trajectory of a swarm motor vehicle on the road section and/or a frequency distribution of the swarm motor vehicles on the road section. Furthermore, the swarm data information regarding a position, a speed, a steering wheel angle and / or a yaw rate of a swarm motor vehicle.

The module 10 can determine a prediction for the driving path. In this case, for example, sensor data can serve as a basis, which includes information regarding a position, a speed, a steering wheel angle and/or a yaw rate of the motor vehicle. A corrected driving path is then determined based on the prediction for the driving path and swarm data, and information relating to the corrected driving path is transmitted to the automatic distance control system 20 . The automatic distance control system 20 regulates and/or controls one's own motor vehicle based on the information regarding the cornering speed.

It goes without saying that the module 10 can also directly determine a corrected driving path without first determining a prediction for a driving path based on the sensor data.

When creating the corrected driving path, a determined number of lanes and a course of the lanes on the roadway section are taken into account, based on the trajectory of a swarm motor vehicle and / or a frequency distribution of the swarm motor vehicles on the number of lanes and the course of the Road section can be closed. In the case of the corrected driving path, a width and/or a course of the driving path can therefore be modified.

It goes without saying that the module 10 can be part of an on-board computer, a navigation system and/or particularly preferably the automatic distance control system 20 . As a result, the costs and the installation space requirements can be kept low.

In 3 a system 22 according to the invention with an at least partially assisted driving motor vehicle 24 and a swarm data pool 18 is shown. Motor vehicle 24 has an automatic distance control system 20 and a module 10 . Furthermore, sensors 26 are arranged on the motor vehicle 24 . The sensors 26 can be, for example, a lidar sensor in a vehicle front, a front camera, a steering angle, acceleration, GPS and/or speed sensor.

The module 10 can receive and analyze sensor data from the sensors 26 . Furthermore, the module 10 can exchange swarm data with the swarm data pool 18 by means of a communication interface 30 of the motor vehicle 24 .

On the one hand, the module 10 can receive data from the swarm data pool 18 . A correction of the prediction of the driving path or a corrected driving path, as already described above, can then be determined by means of the received swarm data. In particular, the module 10 can receive sensor data from the sensors 26 and determine a corrected driving path based on a weighting of the sensor data and/or the swarm data.

On the other hand, the module 10 can send data to the swarm data pool 18 . In this respect, the motor vehicle 24 acts as a swarm motor vehicle. The sensors 26 can include at least one of the following sensor types, for example: a lateral acceleration sensor, a GPS sensor, a speed sensor and/or a steering angle sensor. The swarm data that is transmitted to the swarm data pool 18 is preferably the sensor data. It goes without saying that further data, in particular pre-processed data relating to a position, speed, acceleration etc. of motor vehicle 24 can be transmitted.

In 4 1 is a schematic representation of a prediction of a driving path 32 when a motor vehicle 24 is traveling on a multi-lane roadway section with two other motor vehicles 34 . Two courses of the prediction of the driving path 32 are shown. A prediction of the driving path 32 when driving straight ahead is shown with dots. For example, such a prediction of the driving path 32 can be determined if no steering wheel lock can be detected or if the lock of the steering wheel indicates straight-ahead driving. A course of the prediction of the driving path 32 is shown in dashed lines when a steering angle lock can be detected.

In a multi-lane section of road, it is unlikely that a cornering is intended when the steering wheel is turned. In most cases, a steering wheel turn indicates a lane change. Sometimes this information does not influence the prediction for the driving path 32 .

In the example shown, none of the other motor vehicles 34 would be detected in the prediction of the driving path 32 . Consequently, none of the motor vehicles 34 would be regulated. In the case of a lane change, the front motor vehicle 34 is in front of the driver's own motor vehicle 24 and would not be recognized or recognized only late. This leads to an increased risk of accidents.

In 5 a system 22 according to the invention is shown schematically, with a motor vehicle 24 of the system 22 according to the invention, as in 4 shown, performs a lane change. For reasons of clarity, the motor vehicle 24 has been shown in a schematically simplified manner. It goes without saying that the motor vehicle 24 at least partially 3 features shown and described.

in the in 5 The situation shown receives the motor vehicle 24 from the swarm data pool 18 while driving swarm data. The module 10 determines a corrected driving path 36 based on the swarm data and sensor data of the sensor 26. The prediction of the driving path 32 without swarm data is shown in dashed lines.

Based on the swarm data, the module 10 determines that it is a multi-lane roadway section that is essentially straight. Therefore, the detected steering angle can be interpreted better. The module 10 recognizes that the driver's vehicle 24 is changing lanes and determines a corrected driving path 36 which at least partially encompasses both lanes. In this way, the motor vehicle 34 driving ahead, which is in the lane into which the driver's own vehicle is changing, can be recognized and used as a control object for the automatic distance control system 20 .

In 6 The determination of a corrected driving path 36 from data of a swarm 38 of swarm motor vehicles 40, a prediction for a driving path 32 and sensor data from sensors 26 is shown schematically.

The swarm 34 of motor vehicles 24 can have different vehicle types that have previously driven through a section of road for which the corrected driving path 36 is to be created.

Based on the trajectory of the swarm motor vehicles 40 and/or a frequency distribution of the swarm motor vehicles 40, a number of lanes and a course of the lanes on the road section can be determined from the swarm data. Based on this data and preferably the prediction for the driving path 32 , the corrected driving path 36 can then be determined and transmitted to the automatic distance control system 20 .

In 7 The steps of a method according to the invention for determining a corrected driving path 36 for an automatic distance control system 20 of an at least partially assisted driving motor vehicle 24 are shown schematically.

In a first step S1, input data is received, comprising sensor data from a sensor 26 of motor vehicle 24 and swarm data with information about a roadway section of a roadway in front of motor vehicle 24. Receiving S1 of input data includes receiving swarm data from a swarm data pool 18 with Information from swarm motor vehicles 40. In a second step S2, a prediction for the driving path 32 is determined based on the sensor data. In a third step S3, the corrected driving path 36 is then determined based on the prediction for the driving path 32 and the swarm data. Finally, in a fourth step S4, information relating to the corrected driving path 36 is transmitted.

Reference List

10

module

12

input interface

14

analysis unit

16

output interface

18

Swarm Data Pool

20

automatic distance control machine

22

system

24

motor vehicle

26

sensor

30

communication interface

32

Prediction for travel tube

34

another motor vehicle

36

corrected driving tube

38

swarm

40

swarm motor vehicle

S1 - S4

process steps

Claims (10)

Module (10) for determining a corrected driving path (36) for an automatic distance control system (20) of an at least partially assisted driving motor vehicle (24), with: - an input interface (12) for receiving input data, comprising sensor data from a sensor (26) of the motor vehicle (24) and swarm data with information on a roadway section of a roadway in front of the motor vehicle (24); - An analysis unit (14) for determining a prediction for the driving path (32) based on the sensor data; - An output interface (16) for transmitting information relating to the driving path (32, 36), characterized in that the input data include swarm data from a swarm data pool (18) with information from swarm motor vehicles (40) and the analysis unit (14) is designed to determine the corrected driving path (36) based on the prediction for the driving path (32) and the swarm data. Module (10) after claim 1 , characterized in that the swarm data include information relating to a trajectory of a swarm motor vehicle (40) on the road section and / or a frequency distribution of the swarm motor vehicles (40) on the road section. Module (10) according to the preceding claim, characterized in that the analysis unit (14) is designed to calculate a number of lanes and to determine a course of the lanes on the roadway section. Module (10) according to any one of the preceding claims, characterized in that the sensor data is information relating to a position, a speed, a steering wheel angle and/or a yaw rate of the motor vehicle (24) and/or a position, a speed and/or a yaw rate of objects on the road section. Module (10) according to one of claims 3 or 4 , characterized in that the analysis unit (14) is designed to determine the corrected driving path (36) based on a weighting of individual information. Module (10) according to one of the preceding claims, characterized in that the module (10), preferably the output interface of the module (10), is designed to transmit sensor data from the motor vehicle (24) to the swarm data pool (18). Motor vehicle (24) with: - A module (10) according to any one of the preceding claims; - An automatic distance control machine (20); and - A sensor (26) for detecting sensor data with information relating to the motor vehicle (24). System (22) for determining a corrected driving path with: a motor vehicle (24) according to the preceding claim and a swarm data pool (18) comprising swarm data, the system (22) being designed to exchange swarm data with the swarm data pool (18). Method for determining a corrected driving path (36) for an automatic distance control system (20) of an at least partially assisted driving motor vehicle (24), comprising the steps: - Receiving (S1) of input data, comprising sensor data from a sensor (26) of the motor vehicle (24) and swarm data with information about a roadway section of a roadway in front of the motor vehicle (24), the receiving of input data including receiving swarm data from a swarm data pool (18) with information from swarm motor vehicles (40); - determining (S2) a prediction for the driving path (32) based on the sensor data; - determining (S3) the corrected driving path (36) based on the prediction for the driving path (32) and the swarm data; - Transmission (S4) of information regarding the corrected driving path. Computer program with program code means to carry out all steps of a method according to the above claim 9 to be carried out when the computer program is executed on a computer or a corresponding computing unit.

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