System and method to generate a lane-level traffic map using vehicle sensor data
Systems and methods are provided for generating a real-time lane-level traffic map based on outbound sensor information. In particular, some embodiments generate lane-level traffic maps using radar sensor information. The populated real-time lane-level traffic maps are shared to other vehicles and may be used by autonomous vehicle systems to maneuver the vehicle.
1. A method comprising:
identifying, based on sensor information received from an ego vehicle, locations of other vehicles traveling in the same direction as the ego vehicle on a multi-lane roadway;
calculating speeds for the other vehicles based on the received sensor information; and
displaying, on a graphical user interface (GUI) of the ego vehicle, a lane-level traffic map for the multi-lane roadway indicating a lane-by-lane traffic condition based on the identified locations and calculated speeds, wherein the lane-level traffic map comprises regions arranged in rows, a respective row represents a respective lane of the multi-lane roadway, and a respective region represents a respective identified location, and wherein displaying the lane-level traffic map comprises determining and generating lengths of regions in the respective row based on at least one of:
speeds of vehicles in the respective lane of the multi-lane roadway;
a time of day;
a speed limit on the multi-lane roadway; and
a road type for the multi-lane roadway.
2. The method of claim 1 , wherein the sensor information is received from a radar sensor of the ego vehicle.
3. The method of claim 1 , wherein generating the lane-level traffic map for the multi-lane roadway occurs between a rapid interval.
4. The method of claim 1 , wherein the lane-by-lane traffic condition identifies speeds of traffic located at the identified locations.
5. The method of claim 1 , wherein generating the lane-level traffic map for the multi-lane roadway further comprises:
receiving a lane-level traffic map for the multi-lane roadway from different vehicles or from a cloud network database; and
merging the lane-level traffic map for the multi-lane roadway with the lane-level traffic map for the multi-lane roadway from the different vehicles or from the cloud network database.
6. The method of claim 1 , wherein generating the lane-level traffic map for the multi-lane roadway further comprises populating the regions based on the identified locations of the other vehicles with a color from a gradient of color based on the calculated speeds of the other vehicles.
7. The method of claim 1 , wherein the lane-level traffic map is sent to an autonomous driving system to facilitate maneuvering in response to the lane-by-lane traffic condition.
8. A vehicle comprising:
one or more outbound sensors;
one or more processors;
memory coupled to the one or more processors to store instructions, which when executed by the one or more processors, cause the vehicle to:
identify, based on sensor information received from the one or more outbound sensors, locations of other vehicles traveling in the same direction as the vehicle on a multi-lane roadway;
calculate speeds for the other vehicles based on the received sensor information;
generate a lane-level traffic map for the multi-lane roadway indicating a lane-by-lane traffic condition based on the identified locations and calculated speeds, wherein the lane-level traffic map comprises regions arranged in rows, a respective row represents a respective lane of the multi-lane roadway, and a respective region represents a respective identified location, and wherein generating the lane-level traffic map comprises determining and generating lengths of regions in the respective row based on at least one of:
speeds of vehicles in the respective lane of the multi-lane roadway;
a time of day;
a speed limit on the multi-lane roadway; and
a road type for the multi-lane roadway; and
execute a maneuver for the vehicle based on the indicated lane-by-lane traffic condition.
9. The vehicle of claim 8 , wherein the one or more sensors comprise a radar sensor.
10. The vehicle of claim 8 , wherein generating the lane-level traffic map for the multi-lane roadway occurs between a rapid interval.
11. The vehicle of claim 8 , wherein the lane-by-lane traffic condition identifies speeds of traffic located at the identified locations.
12. The vehicle of claim 8 , wherein generating the lane-level traffic map for the multi-lane roadway further comprises:
receiving a lane-level traffic map for the multi-lane roadway from different vehicles or from the cloud network database; and
merging the lane-level traffic map for the multi-lane roadway with the lane-level traffic map for the multi-lane roadway from the different vehicles or from the cloud network database.
13. The vehicle of claim 8 , wherein generating the lane-level traffic map for the multi-lane roadway further comprises populating the regions based on the identified locations of the other vehicles with a color from a gradient of color based on the calculated speeds of the other vehicles.
14. A system, comprising:
a graphical user interface (GUI);
one or more processors;
and
memory coupled to the one or more processors to store instructions, which when executed by the one or more processors, cause the system to:
identify, based on sensor information received from an ego vehicle, locations of other vehicles traveling in the same direction as the ego vehicle on the multi-lane roadway;
calculate speeds for the other vehicles based on the received sensor information; and
display, on the GUI, a lane-level traffic map for the multi-lane roadway indicating a lane-by-lane traffic condition based on the identified locations and calculated speeds, wherein the lane-level traffic map comprises regions arranged in rows, a respective row represents a respective lane of the multi-lane roadway, and a respective region represents a respective identified location, and wherein displaying the lane-level traffic map comprises determining and generating lengths of regions in the respective row based on at least one of:
speeds of vehicles in the respective lane of the multi-lane roadway;
a time of day;
a speed limit on the multi-lane roadway; and
a road type for the multi-lane roadway.
15. The system of claim 14 , wherein the sensor information is received from a radar sensor of the ego vehicle.
16. The system of claim 14 , wherein the generating the lane-level traffic map for the multi-lane roadway occurs between a rapid interval.
17. The system of claim 14 , wherein the lane-by-lane traffic condition identifies speeds of traffic located at the identified locations.
18. The method of claim 1 , further comprising executing a maneuver for at least one of the ego vehicle or one or more of the other vehicles based on the indicated lane-by-lane traffic condition.
19. The method of claim 18 , wherein the executed maneuver comprises a lane change.
20. The vehicle of claim 8 , wherein the executed maneuver comprises a lane change.