Classifier hierarchies for traffic light and traffic indicator detection
US-9442487-B1 · Sep 13, 2016 · US
US10018472B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10018472-B2 |
| Application number | US-201615376596-A |
| Country | US |
| Kind code | B2 |
| Filing date | Dec 12, 2016 |
| Priority date | Dec 10, 2015 |
| Publication date | Jul 10, 2018 |
| Grant date | Jul 10, 2018 |
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A computer system operates to determine a traction value for each of a plurality of regions of the road network. A region of the road network for which the traction value is unknown is identified. A vehicle is directed to operate over the region of the road network to obtain additional data that is indicative of a current traction value.
Opening claim text (preview).
What is claimed is: 1. A method for operating a network computer system to maintain information about a road network, the method comprising: determining a traction value for each of a plurality of regions of the road network; identifying a region of the road network for which the traction value is unknown; and directing a vehicle to operate over the region of the road network to obtain additional data that is indicative of a current traction value. 2. The method of claim 1 , wherein determining the traction value includes receiving sensor data from a plurality of vehicles, and determining the traction value by correlating the sensor data to traction values. 3. The method of claim 2 , further comprising: determining the traction value for at least a first set of the plurality of regions using the sensor data. 4. The method of claim 3 , wherein determining the traction value includes extrapolating the traction value for at least a second set of the plurality of regions using traction values determined for the first set of regions. 5. The method of claim 2 , wherein determining the traction value includes applying a timing function to at least some of the determined traction values. 6. The method of claim 5 , wherein the timing function is based on an environmental or roadway condition that is deemed present. 7. The method of claim 6 , wherein the environmental or roadway condition includes at least one of accumulation of precipitation, environmental temperature, amount of wind, time of day, presence of shading, or slope of road. 8. The method of claim 1 , wherein identifying the region of the road network for which the traction value is unknown includes identifying the region for which an existing traction value is deemed out of date. 9. The method of claim 8 , wherein the existing traction value is deemed out of date upon determining that data indicative of the existing traction value for the region has not been updated within a threshold duration of time. 10. The method of claim 9 , further comprising determining the threshold duration of time based on one or more environmental conditions. 11. The method of claim 10 , wherein the one or more environmental conditions includes accumulation of precipitation, environmental temperature, amount of wind, time of day, presence of shading, or slope of road. 12. The method of claim 1 , wherein directing the vehicle to operate over the region of the road network includes instructing an autonomous vehicle to operate over the region. 13. The method of claim 12 , wherein the autonomous vehicle is instructed to operate over the region after determining that no passengers are in the autonomous vehicle. 14. The method of claim 12 , wherein directing the vehicle to operate over the region of the road network includes rerouting the autonomous vehicle to operate over the region when the autonomous vehicle is progressing on a different route to complete an existing trip. 15. The method of claim 1 , wherein directing the vehicle to operate over the region includes instructing an autonomous vehicle to perform a selected driving operation in which the vehicle accelerates, slows, or turns. 16. The method of claim 15 , wherein the autonomous vehicle is instructed to perform the selected driving operation with a magnitude that is outside of a safety threshold. 17. A non-transitory computer readable medium that stores instructions, which when executed by one or more processors of a computer system, cause the computer system to perform operations that include: determining a traction value for each of a plurality of regions of a road network; identifying a region of the road network for which the traction value is unknown; and directing a vehicle to operate over the region of the road network to obtain additional data that is indicative of a current traction value. 18. The non-transitory computer readable medium of claim 17 , wherein determining the traction value includes receiving sensor data from a plurality of vehicles, and determining the traction value by correlating the sensor data to traction values. 19. The non-transitory computer readable medium of claim 18 , further comprising instructions for: determining the traction value for at least a first set of the plurality of regions using the sensor data. 20. The non-transitory computer readable medium of claim 19 , wherein determining the traction value includes extrapolating the traction value for at least a second set of the plurality of regions using traction values determined for the first set of regions. 21. A network computer system to maintain information about a road network, the network computer system comprising: a memory resource to store instructions; and one or more processors using the instructions stored in the memory resource to perform operations including: determining a traction value for each of a plurality of regions of the road network; identifying a region of the road network for which the traction value is unknown; and directing a vehicle to operate over the region of the road network to obtain additional data that is indicative of a current traction value. 22. The network computer system of claim 21 , wherein determining the traction value includes receiving sensor data from a plurality of vehicles, and determining the traction value by correlating the sensor data to traction values. 23. The network computer system of claim 22 , further comprising instructions for: determining the traction value for at least a first set of the plurality of regions using the sensor data. 24. The network computer system of claim 23 , wherein determining the traction value includes extrapolating the traction value for at least a second set of the plurality of regions using traction values determined for the first set of regions.
Degree of grip · CPC title
specially adapted for navigation in a road network · CPC title
Input parameters relating to infrastructure · CPC title
Road friction coefficient · CPC title
Operations & Transport · mapped topic
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