PATENT CLAIM ANALYSIS

Application Number: 15956339
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2019-10
Patent Classification: ["701", "469000"]

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 cell-density image of the first road segment, where the cell-density image represents a volume of probe data points at each of a plurality of cells of a grid overlaid on the first road segment; applying a deconvolution method to the cell-density image to obtain a refined cell-density image having a lower degree of data point spread; determining, from the refined cell-density image, a number of paths along the first road segment, where each path represents a lane; and computing, from the refined cell-density image, lane-level properties of the probe data of the first road segment.

Claim (Index 10):
The computer program product of  claim 9 , the program code instructions to compute, from the refined cell-density image, lane-level properties of the probe data of the first road segment comprises program code instructions to:\n generate digital map data having a number of road segment lanes corresponding to the number of trajectories at positions corresponding to the trajectories on the first road segment; and provide for at least semi-autonomous vehicle control or navigation assistance using the generated digital map data.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 91.0
- Lexical Diversity: 2.7377
- Patent Class: 701.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15956316', '15654066', '15656499', '14511603', '14572197']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4428178478360036
- 35 USC 102 Novelty (BERT): 0.5634158319065095
- Combined Prediction Score: 0.4548776462430542
- Mean Citation Score: 297.584982
- Max Citation Score: 444.35086
- Similarity Product: 366.5026086577558

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test