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 19):
The method of  claim 15 , wherein the probe data points each include a timestamp, wherein generating, from the probe data points associated with a first road segment, a spatiotemporal cell-density image dimension of the first road segment comprises:\n separating the probe data points into at least two different periods of time based on the respective timestamps; and generating, from the probe data points associated with the first road segment and associated with each period of time, a spatiotemporal cell-density image of the first road segment.

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): 0.4449974265012441
- 35 USC 102 Novelty (BERT): 0.5590598851479022
- Combined Prediction Score: 0.4564036723659099
- Mean Citation Score: 297.584982
- Max Citation Score: 444.35086
- Similarity Product: 331.5854024247384

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