Method of generating expected average speed of travel
A method of generating map data indicating a deviation from expected jam conditions on a segment of a plurality of segments in an area covered by an electronic map, the segment having associated therewith a jam probability indicating the likelihood of a jam on that segment. The method comprises establishing an expected jam condition for the segment based on the jam probability of that segment, and then obtaining live data indicating the jam conditions on at least one of the plurality of other segments in the area. A revised jam condition can then be established for the segment using the obtained live data.
1. A method of predicting an existence of a jam on a segment of an electronic map, the electronic map being representative of a network of segments in an area covered by the electronic map, each segment representing a respective navigable segment of the network and having associated therewith a stored jam probability indicating a likelihood likelihood of a jam on that segment calculated using historic travel data, the method comprising:
determining a set of a plurality of segments of the electronic map;
obtaining live travel data indicative of current or relatively current traffic conditions on at least some of the plurality of segments in the set;
using the stored jam probability for a givena given segment in the set and the live travel data to predict whether the given segment is jammed or not jammed by:
calculating an adjusted jam probability for the given segment using the stored jam probability for the given segment and the live travel data, the calculating including weighting the live travel data for the calculating so that an effect of the live travel data on the adjusted jam probability is dependent on the live travel data obtained, wherein, when less than a cut-off threshold worth of live travel data is obtained for the given segment, the live travel data is weighed so that the live travel data has no effect on the adjusted jam probability;
using the adjusted jam probability for the given segment to predict whether the given segment is jammed or not jammed; and
outputting, to navigation devices, a jam warning for the given segment when the given segment is predicted to be jammed, the jam warning including information to be used by the navigation devices for determining a speed of traffic on the given segment for performing navigation operations.
2. The method of claim 1 , wherein the given segment is predicted to be jammed when the adjusted jam probability associated with the given segment exceeds a predefined value.
3. The method of claim 2 , wherein the predefined value is based on the live travel data.
4. The method of claim 1 , wherein using the value of the stored jam probability for the given segment to make the prediction whether the given segment is jammed or not jammed includes predicting the given segment to be jammed when the stored jam probability exceeds a predefined value, the predefined value being based on the live travel data.
5. The method of claim 1 , wherein each of the plurality of segments have multiple time dependent jam probabilities associated therewith reflecting variations in jam probability over time for selected time intervals.
6. The method of claim 1 , wherein the output jam warning for the given segment comprises an expected average speed of travel across the segment.
7. The method of claim 6 , wherein each of the plurality of segments have associated therewith a stored jam speed calculated using historic travel data and indicating the speed on that segment when that segment is considered jammed, and wherein the expected average speed of travel is the stored jam speed or a speed based thereon.
8. A non-transitory machine readable medium comprising instructions which, when executed by a machine, cause that machine to perform the method of claim 7 .
9. The method of claim 1 , wherein calculating the adjusted jam probability for the given segment includes:
using a value of the stored jam probability for the given segment to make a prediction whether the given segment is jammed or not jammed;
examining the live travel data including the live travel data for the other segments in the set for consistency with the prediction of whether the given segment is jammed or not jammed; and
overriding the prediction of whether the given segment is jammed or not jammed when a specified inconsistency is found.
10. The method of claim 1 , wherein:
traffic conditions on the given segment are influenced by other traffic conditions on at least one other segment in the set of the plurality of segments; and
the calculating includes determining a value for the adjusted jam probability for the given segment based in part on a consistency of live travel data for the at least one other segment with a respective jam prediction for the at least one other segment.
11. The method of claim 1 , wherein:
obtaining the live travel data includes obtaining supporting data as well as live travel times for at least the given segment; and
weighting the live travel data when calculating the adjusted jam probability for the given segment includes weighting the supporting data relative to the live travel times based on whether the supporting data meets at least one supporting data condition.
12. A system arranged to predict an existence of a jam on a segment of an electronic map, the electronic map being representative of a network of segments in an area covered by the electronic map, each segment representing a respective navigable segment of the network and having associated therewith a stored jam probability indicating a likelihood of a jam on that segment calculated using historic travel data, the system comprising at least one processor arranged to:
determine a set of a plurality of segments of the electronic map;
obtain live travel data indicative of current or relatively current traffic conditions on at least some of the plurality of segments in the set;
use the stored jam probability for a given segment in the set and the live travel data to predict whether the given segment is jammed or not jammed by:
calculating an adjusted jam probability for the given segment using the stored jam probability for the given segment and the live travel data, the calculating including weighting the live travel data for the calculating so that an effect of the live travel data on the adjusted jam probability is dependent on the live travel data obtained, wherein, when less than a cut-off threshold worth of live travel data is obtained for the given segment, the live travel data is weighed so that the live travel data has no effect on the adjusted jam probability;
using the adjusted jam probability for the given segment to predict whether the given segment is jammed or not jammed; and
output, to navigation devices, a jam warning for the given segment when the given segment is predicted to be jammed, the jam warning including information to be used by the navigation devices for determining a speed of traffic on the given segment for performing navigation operations.
13. The system of claim 12 , wherein the given segment is predicted to be jammed when the adjusted jam probability associated with the given segment exceeds a predefined value.
14. The system of claim 12 , wherein using the value of the stored jam probability for the given segment to make the prediction whether the given segment is jammed or not jammed includes predicting the given segment to be jammed when the stored jam probability exceeds a predefined value, the predefined value being based on the live travel data.
15. The system of claim 12 , wherein calculating the adjusted jam probability for the given segment includes:
using a value of the stored jam probability for the given segment to make a prediction whether the given segment is jammed or not jammed;
examining the live travel data including the live travel data for the other segments in the set for consistency with the prediction of whether the given segment is jammed or not jammed; and
overriding the prediction of whether the given segment is jammed or not jammed when a specified inconsistency is found.
16. The system of claim 12 , wherein:
traffic conditions on the given segment are influenced by other traffic conditions on at least one other segment in the set of the plurality of segments; and
the calculating includes determining a value for the adjusted jam probability for the given segment based in part on a consistency of live travel data for the at least one other segment with a respective jam prediction for the at least one other segment.
17. The system of claim 12 , wherein:
obtaining the live travel data includes obtaining supporting data as well as live travel times for at least the given segment; and
weighting the live travel data when calculating the adjusted jam probability for the given segment includes weighting the supporting data relative to the live travel times based on whether the supporting data meets at least one supporting data condition.