Driver assistance system and method

1. A driver assistance system for an ego vehicle, comprising:

a GPS receiver configured to determine a coarse geolocation measurement of the ego vehicle;

a camera configured to measure a visual appearance of each of at least one static feature located in a vicinity of the ego vehicle; and

an electronic control unit configured to:

using the at least one measurement, calculate a relative position of each of the at least one static feature and the ego vehicle;

using a map, identify a real-world location of the at least one static feature;

calculate a static feature measurement of a location of the ego vehicle using the relative position of the at least one static feature and the ego vehicle and the real-world location of the at least one static feature;

receive the coarse geolocation measurement from the GPS receiver;

identify an uncertainty margin surrounding the coarse geolocation measurement and defined by an extent of uncertainty in the coarse geolocation measurement; and

combine the coarse geolocation measurement of the ego vehicle with the static feature measurement of the location of the ego vehicle to form a fine geolocation position;

wherein the system further includes an inertial measurement unit that is configured to measure at least one ego vehicle motion parameter;

wherein the at least one static feature is located within the uncertainty margin; and

wherein the at least one ego vehicle motion parameter is used in determining a position of the ego vehicle in response to a predetermined period of time elapsing since the calculation of the static feature measurement.

2. The driver assistance system according to claim 1 , further comprising, wherein the system is further configured to use the at least one measurement of each of two or more static features in the calculation of the static feature measurement of the location of the ego vehicle.

3. The driver assistance system according to claim 1 , further comprising, wherein the at least one static feature is a transition between a dashed line marking region and solid line marking region of a road on which the ego vehicle travels.

4. The driver assistance system according to claim 1 , further comprising, wherein the system is further configured to using the fine geolocation position, calculate a traffic lane along which the ego vehicle is most likely to be travelling.

5. The driver assistance system according to claim 1 , further comprising, wherein the system is further configured to determine a sub-region of the map in which to identify the real-world location of the at least one static feature.

6. The driver assistance system according to claim 5 , further comprising, wherein the sub-region is based on the uncertainty margin of the course geolocation measurement.

7. The driver assistance system according to claim 5 , further comprising, wherein the system is further configured to determine whether or not the at least one static feature is identified uniquely within the sub-region of the map.

8. The driver assistance system according to claim 7 , further comprising, wherein if the at least one static feature is not identified uniquely, the system is configured to wait to receive the at least one measurement of the visual appearance of at least one further static feature located in the vicinity of the ego vehicle.

9. The driver assistance system according to claim 1 , further comprising, wherein the coarse geolocation measurement includes at least one of an ego vehicle latitude, an ego vehicle longitude, and an ego vehicle heading.

10. The driver assistance system according to claim 1 , further comprising, wherein the driver assistance system is an autonomous driving system.

11. A method for a driver assistance system for an ego vehicle, the method comprising:

performing at least one measurement of a visual appearance of each of at least one static feature located in a vicinity of the ego vehicle;

using the at least one measurement, calculating a relative position of each of the at least one static feature and the ego vehicle;

using a map, identifying a real-world location of the at least one static feature;

calculating a static feature measurement of a location of the ego vehicle using the relative position of the static feature and the ego vehicle and the real world location of the at least one static feature;

receiving, from a GPS receiver, a coarse geolocation measurement of the ego vehicle;

identifying an uncertainty margin surrounding the coarse geolocation measurement and defined by an extent of uncertainty in the coarse geolocation measurement, wherein the at least one static feature is located within the uncertainty margin;

combining the course geolocation measurement of the ego vehicle with the static feature measurement of the location of the ego vehicle to form a fine geolocation position;

measuring, by an inertial measurement unit, at least one ego vehicle motion parameter; and

using the at least one ego vehicle motion parameter to determine a position of the ego vehicle in response to a predetermined period of time elapsing since the calculating the static feature measurement.

12. The method of claim 11 further comprising the steps of, using the at least one measurement of each of two or more static features in the calculation of the static feature measurement of the location of the ego vehicle.

13. The method of claim 11 further comprising the steps of, using the fine geolocation position, calculate a traffic lane along which the ego vehicle is most likely to be travelling.

14. The method of claim 11 further comprising the steps of, wherein the coarse geolocation measurement includes an ego vehicle latitude, an ego vehicle longitude, and an ego vehicle heading.

15. The method of claim 11 further comprising the steps of, wherein the driver assistance system is an autonomous driving system.