Lane-level geometry and traffic information

A computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code instructions stored therein, the computer-executable program code instructions comprising program code instructions to:

• receive probe data points associated with a plurality of vehicles, each probe data point received from a probe apparatus of a plurality of probe apparatuses, each probe apparatus comprising one or more sensors and being onboard a respective vehicle, wherein each probe data point comprises location information associated with the respective probe apparatus;
• for each of the probe data points, determine a location and a road segment corresponding to the location;
• generate, from the probe data points associated with a first road segment, a probe density histogram for the first road segment, wherein the probe density histogram represents a volume of probe data points at each of a plurality of positions across a width of the first road segment;
• apply a deconvolution method to the probe density histogram to obtain a multi-modal histogram;
• determine, from the multi-modal histogram, a number of statistically significant peaks, wherein each statistically significant peak represents a lane of the first road segment;
• compute, from the multi-modal histogram, lane-level properties of the probe data of the first road segment;
• and
• store the computed lane-level properties of the probe data of the first road segment to augment a geographic database.

A method for establishing lane-level data from probe data comprising:

• receiving probe data points associated with a plurality of vehicles, each probe data point received from a probe apparatus of a plurality of probe apparatuses, each probe apparatus comprising one or more sensors and being onboard a respective vehicle, wherein each probe data point comprises location information associated with the respective probe apparatus;
• for each of the probe data points, determining a location and a road segment corresponding to the location;
• generating, from the probe data points associated with a first road segment, a probe density histogram for the first road segment, wherein the probe density histogram represents a volume of probe data points at each of a plurality of positions across a width of the first road segment;
• applying a deconvolution method to the probe density histogram to obtain a multi-modal histogram;
• determining, from the multi-modal histogram, a number of statistically significant peaks, wherein each statistically significant peak represents a lane of the first road segment;
• computing, from the multi-modal histogram, lane-level properties of the probe data of the first road segment;
• and
• providing data for at least one of navigational assistance or at least semi-autonomous vehicle control based on the computed lane-level properties of the probe data of the first road segment.