Lane-level geometry and traffic information
First Claim
1. A mapping system comprising:
- a memory comprising map data; and
processing circuitry configured 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
provide 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.
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Accused Products
Abstract
Provided herein is a method for establishing lane-level data from probe data. Methods may include receiving probe data points associated with a plurality of vehicles; determining, for each of the probe data points, a location and 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, where 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, where each statistically significant peak represents a lane of the first road segment; and computing, from the multi-modal histogram, lane-level properties of the probe data of the first road segment.
32 Citations
20 Claims
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1. A mapping system comprising:
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a memory comprising map data; and processing circuitry configured 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 provide 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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. 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:
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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. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A method for establishing lane-level data from probe data comprising:
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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. - View Dependent Claims (18, 19, 20)
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Specification