Method for laterally controlling a motor vehicle on a road having two lanes and motor vehicle
Technologies and techniques for laterally controlling a motor vehicle on a road, where a roadway marking assigned to a driver's side of the motor vehicle is assigned to a lane type based on sensor data. The lane type characterizes whether the roadway marking is assigned to an ego lane on which the motor vehicle is to be guided, or whether it is assigned to a neighboring lane adjacent to the ego lane. The roadway marking is also assigned to the lane type, based on swarm data, and the lane type assigned to the roadway marking is established as the lane type that is determined as a function of the swarm data when the sensor lane type and the swarm data lane type diverge. The motor vehicle is laterally controlled as a function of the established lane type of the roadway marking assigned to the driver's side of the motor vehicle.
1. A method for laterally controlling a motor vehicle on a road, comprising:
assigning a lane type to a roadway marking on a driver's side of the motor vehicle using sensor data, wherein the lane type characterizes whether the roadway marking is (i) assigned to an ego lane of the motor vehicle, or (ii) assigned to a neighboring lane adjacent to the ego lane;
assigning the lane type to the roadway marking using swarm data;
determining that the assigned lane type using sensor data and the assigned lane type using swarm data diverge;
establishing the lane type to the roadway marking on the driver's side of the motor vehicle as a function of the swarm data, based on the divergence;
laterally controlling the motor vehicle via an electronic computing device in an assisted manner as a function of the established lane type of the roadway marking that is assigned to the driver's side of the motor vehicle.
2. The method according to claim 1 , wherein the motor vehicle is laterally controlled based on the sensor data.
3. The method according to claim 1 , wherein the motor vehicle is laterally controlled based on the swarm data.
4. The method according to claim 1 , wherein the lane type assigned to the roadway marking is established as the lane type that is determined as a function of the sensor data, when a lane type determined based on the sensor data and a lane type determined based on the swarm data for a roadway marking that is assigned to the passenger side of the motor vehicle diverge.
5. The method according to claim 1 , wherein the sensor data comprises camera data based on which the roadway marking that is assigned to the driver's side of the motor vehicle is analyzed by way of an image recognition method.
6. The method according to claim 1 , wherein the lane type assigned to the roadway marking is established as the lane type that is determined as a function of the swarm data when the swarm data meets at least one predefined quality criterion.
7. The method according to claim 6 , wherein:
a match rate between parameters determined from the swarm data and parameters determined from the sensor data for a defined route section is specified as the quality criterion, and/or
a localization quality of a localization of the motor vehicle on the road based on the swarm data is specified as a quality criterion.
8. The method according to claim 1 , wherein the lane type assigned to the roadway marking is established as the lane type that is determined as a function of the swarm data under one or more of the following conditions:
while a predefined time interval is ongoing,
while the motor vehicle is covering a predefined route,
while the motor vehicle is being moved in the driving direction at a speed within a predefined speed range,
when the road has a curvature above a predefined curvature limit value,
when the road including the roadway marking has a width within a predefined width range, and/or
when the motor vehicle has a distance with respect to a further roadway marking that is assigned to a passenger side of the motor vehicle within a predefined distance range.
9. The method according to claim 1 , wherein the lane type assigned to the roadway marking that is assigned to the driver's side of the motor vehicle is established as the lane type that is determined as a function of the sensor data when the lane type determined based on the sensor data and the lane type determined based on the swarm data are identical.
10. A motor vehicle, configured for lateral control on a road, comprising:
sensors for providing sensor data;
communications for receiving swarm data;
an electronic computing device, operatively coupled to the sensors and communications, the electronic computing device being configured to facilitate lateral control of the motor vehicle; and
a processing apparatus, operatively coupled to the electronic computing device, communications and the sensors, wherein the processing apparatus is configured to assign lane type to a roadway marking on a driver's side of the motor vehicle using sensor data, wherein the lane type characterizes whether the roadway marking is (i) assigned to an ego lane of the motor vehicle, or (ii) assigned to a neighboring lane adjacent to the ego lane;
assign the lane type to the roadway marking using the swarm data;
determine that the assigned lane type using sensor data and the assigned lane type using swarm data diverge;
establish the lane type to the roadway marking on the driver's side of the motor vehicle as a function of the swarm data, based on the divergence; and
laterally control the motor vehicle via the electronic computing device in an assisted manner as a function of the established lane type of the roadway marking that is assigned to the driver's side of the motor vehicle.
11. The motor vehicle of claim 10 , wherein the motor vehicle is laterally controlled based on the sensor data.
12. The motor vehicle of claim 10 , wherein the motor vehicle is laterally controlled based on the swarm data.
13. The motor vehicle of claim 10 , wherein the lane type assigned to the roadway marking is established as the lane type that is determined as a function of the sensor data, when a lane type determined based on the sensor data and a lane type determined based on the swarm data for a roadway marking that is assigned to the passenger side of the motor vehicle diverge.
14. The motor vehicle of claim 10 , wherein the sensor data comprises camera data based on which the roadway marking that is assigned to the driver's side of the motor vehicle is analyzed by way of an image recognition method.
15. The motor vehicle of claim 10 , wherein the lane type assigned to the roadway marking is established as the lane type that is determined as a function of the swarm data when the swarm data meets at least one predefined quality criterion.
16. The motor vehicle of claim 15 , wherein:
a match rate between parameters determined from the swarm data and parameters determined from the sensor data for a defined route section is specified as the quality criterion, and/or
a localization quality of a localization of the motor vehicle on the road based on the swarm data is specified as a quality criterion.
17. The motor vehicle of claim 10 , wherein the lane type assigned to the roadway marking is established as the lane type that is determined as a function of the swarm data under one or more of the following conditions:
while a predefined time interval is ongoing,
while the motor vehicle is covering a predefined route,
while the motor vehicle is being moved in the driving direction at a speed within a predefined speed range,
when the road has a curvature above a predefined curvature limit value,
when the road including the roadway marking has a width within a predefined width range, and/or
when the motor vehicle has a distance with respect to a further roadway marking that is assigned to a passenger side of the motor vehicle within a predefined distance range.
18. The motor vehicle according to claim 10 , wherein the lane type assigned to the roadway marking that is assigned to the driver's side of the motor vehicle is established as the lane type that is determined as a function of the sensor data when the lane type determined based on the sensor data and the lane type determined based on the swarm data are identical.
19. A method for laterally controlling a motor vehicle on a road, comprising:
assigning a lane type to a roadway marking on a driver's side of the motor vehicle using sensor data, wherein the lane type characterizes whether the roadway marking is (i) assigned to an ego lane of the motor vehicle, or (ii) assigned to a neighboring lane adjacent to the ego lane;
assigning the lane type to the roadway marking using swarm data;
determining that the assigned lane type using sensor data and the assigned lane type using swarm data diverge;
establishing the lane type to the roadway marking on the driver's side of the motor vehicle as a function of the swarm data, based on the divergence;
laterally controlling the motor vehicle via an electronic computing device in an assisted manner as a function of the established lane type of the roadway marking that is assigned to the driver's side of the motor vehicle,
wherein the motor vehicle is laterally controlled based on one of the sensor data or the swarm data.
20. The method according to claim 19 , wherein the lane type assigned to the roadway marking is established as the lane type that is determined as a function of the sensor data, when a lane type determined based on the sensor data and a lane type determined based on the swarm data for a roadway marking that is assigned to the passenger side of the motor vehicle diverge.