PATENT CLAIM ANALYSIS

Application Number: 15870870
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2019-07
Patent Classification: ["382", "103000"]

Abstract:
A method receives situation data including images from vehicles; clusters, into an image cluster, the images included in the situation data of vehicle(s) located in a geographic region from among the vehicles; locates related situation object(s) in image(s) of the image cluster; matches images from different vehicles in the image cluster, the matched images having corresponding feature(s) of the related situation object(s); determines three-dimensional (3D) sensor coordinates of the related situation object(s) relative to a sensor position of a target vehicle associated with at least one matched image, using the corresponding feature(s) of the related situation object(s) in the matched images; converts the 3D sensor coordinates of the related situation object(s) to geolocation coordinates of the related situation object(s) using geolocation data of the different vehicles associated with the matched images; and determines a coverage area of a traffic situation based on the geolocation coordinates of the related situation object(s).

Claim (Index 6):
The method of  claim 5 , wherein determining that the localization difference between the first coverage area and the second coverage area satisfies the difference threshold includes:\n determining one or more first lanes associated with the first coverage area; determining one or more second lanes associated with the second coverage area; and determining that the one or more second lanes are different from the one or more first lanes.

Metadata:
- Claim Count in Document: 48.0
- Percentile: 86.0
- Lexical Diversity: 3.16129
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['12901645', '15529942', '15081756', '13011036', '13181822']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3014475430364245
- 35 USC 102 Novelty (BERT): 0.5046144449805032
- Combined Prediction Score: 0.3217642332308324
- Mean Citation Score: 173.900792
- Max Citation Score: 186.35036
- Similarity Product: 114.88301245695352

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test