PATENT CLAIM ANALYSIS

Application Number: 15914760
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-09
Patent Classification: ["340", "905000"]

Abstract:
An approach is provided for automatically detecting a merge lane traffic jam. The approach involves, for example, determining a plurality of road links in proximity to a merge point comprising a highway and a ramp. The method also involves processing probe data collected from the plurality of road links to classify the plurality of road links, one or more sublinks of the plurality of road links, or a combination thereof into at least one of a highway upstream class, a merging area class, a highway downstream class, a ramp downstream class, and a ramp upstream class. The method further involves determining vehicle speed data for the highway upstream class, the merging area class, the highway downstream class, the ramp downstream class, the ramp upstream class, or a combination thereof. The method further involves automatically determining an occurrence of the merge lane traffic jam based on the vehicle speed data.

Claim (Index 10):
The method of  claim 1 , wherein the highway includes a merge lane and one or more other lanes, the method further comprising:\n determining a lane-level bi-modality with respect to the merge lane and the one or more other lanes based on the vehicle speed data to indicate the occurrence of the merge lane traffic jam, wherein the merge lane traffic jam message is presented on the device that is traveling in the merge lane of the highway corresponding to the highway upstream class; and wherein the merge lane traffic jam message includes instructions to move from the merge lane to the one or more other lanes.

Metadata:
- Claim Count in Document: 5.0
- Percentile: 90.0
- Lexical Diversity: 2.78333
- Patent Class: 340.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15142336', '11355011', '15370337', '14050849', '14755927']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6741312983642236
- 35 USC 102 Novelty (BERT): 0.4966728706536359
- Combined Prediction Score: 0.6563854555931649
- Mean Citation Score: 200.860748
- Max Citation Score: 237.59218
- Similarity Product: 185.0418763352573

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